Commit Graph

66 Commits (6e9c849e4a4e6ae87c8876b6b3929d6581c20f39)

Author SHA1 Message Date
Yurii Shyrma 753ce28a92
Shyrma sqrtm (#429)
* - start working on implementation of sqrtm op

Signed-off-by: Yurii <iuriish@yahoo.com>

* - improving householder procedure

Signed-off-by: Yurii <iuriish@yahoo.com>

* - further polishing householder stuff

Signed-off-by: Yurii <iuriish@yahoo.com>

* - polishing hh pivoting qr procedure

Signed-off-by: Yurii <iuriish@yahoo.com>

* - polishing BiDiagonalUp procedure

Signed-off-by: Yurii <iuriish@yahoo.com>

* - polishing householder sequence class

Signed-off-by: Yurii <iuriish@yahoo.com>

* - polishing jacobi svd class

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* - polishing svd stuff 1

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* - polishing svd stuff 2

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* - implementation and testing class which performs Hessenberg decomposition of square matrix

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* - add static method to JacobiSVD class which makes the continuous Givens rotation generation algorithm

Signed-off-by: Yurii <iuriish@yahoo.com>

* - implementation and testing auxiliary methods of Schur decomp class

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* some references here and there

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* - trying figure out difference between eigen and our Schur alg

Signed-off-by: Yurii <iuriish@yahoo.com>

* - testing fixing bugs in Schur decomposition op

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* - start to implement class which performs calculation of eigen values and vectors

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* - add to EigenValsAndVecs method which calculates complex eigen vectors

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* - testing and fixing bugs in EigenValsAndVecs class

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* - implementation and testing triangularSolver class

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* Added a 2D routine for triangular systems solve.

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* Refactored triangularSolve2D routine and tests.

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* Refactored another test for triangularSolve2D.

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* Refactored test for triangularSolve for vector-bar case.

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* Refactored triangularSolve2D routine and tests.

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* - implementation of FullPivLU class

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* - fix bugs in FullPivLU::solve method

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* - correct permutation vector in FullPivLU::solve

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* - correct include headers

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* - implementation of Sqrtm class

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* - testing and fixing bugs in Sqrtm class

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* - include sqrtm classes to cuda folder, investigate in what places synchronization doesn't work

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* Added implementation for cuda triangularSolve2D and also refactored triangularSolve2D for cpu.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Eliminated waste implementations.

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* - make offset calculation faster in t<> methods

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* - rename refference T& NDArray::t<> method

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* - further work on cuda sqrtm

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* - provide correct synchronization to device in Sqrtm class

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* - add tests for sqrtm op

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* - correct fails which appeared while testing on jenkins

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* - trying to find out mistake in svd::deflation method

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* Revert "- trying to find out mistake in svd::deflation method"

This reverts commit 19d37baddbc509028e4bc67bc932fe7449becdb6.

* Revert "- trying to find out mistake in svd::deflation method"

This reverts commit 19d37baddbc509028e4bc67bc932fe7449becdb6.

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* - change call semantic of r<> and t<> methods

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* - ged rid of ambiguity in * operator overloads for windows buikd

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* - get rid of ambiguity in * operator overloads for windows build 2

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* - get rid of ambiguity in * operator overloads for windows build 3

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* - resolve conflicts with master

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* cmakelists updated

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* - minor fix in merge cpu helper - make use of reference getter

Signed-off-by: Yurii <iuriish@yahoo.com>

Co-authored-by: raver119 <raver119@gmail.com>
Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-14 18:06:13 +03:00
Abdelrauf 69d91e272a
- new implementations for Index Reductions (#421)
* - new implementations for Index Reductions
- small fix in the legacy reduction
- disabled index reduction bench tests inside Playground

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* Allow LIBND4J_TYPES

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* index reduction stuff split into bunch of units

* meh

* IMax switched to new impl

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* minor fix + test

* minor fix

* index range fix

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* noop on empty outputs

* minor fix

* minor fix

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* ArgMax replaces IMax

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* argmax/argmin/argamax/argamin shape functions updated

* ArgAmax/ArgAmin/ArgMin replaces IAMax/IAMin/IMin

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* argmax/argmin/argamax/argamin CUDA

* IMax replaced in dl4j

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* Codegen output

* imports fixed

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* fix compilation issue

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* Auto-generate compilation units

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* Should fix NDArray refactored function calls in indexReductions.cu

Signed-off-by: Abdelrauf <rauf@konduit.ai>

Co-authored-by: raver119@gmail.com <raver119@gmail.com>
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-05-14 13:41:55 +03:00
raver119 05c0f12c73
bump up shared memory (#449)
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2020-05-11 16:55:23 +03:00
raver119 f0adb6f788
[WIP] minor fixes (#447)
* couple of tests disabled

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* few syncs removed, some logging added

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* some logging added

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* some logging added

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* fix min num_threads

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* fixed wrong release function for scalarPointer

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2020-05-11 15:41:43 +03:00
raver119 320924278d
Legacy API changes (#441)
* initial commit

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* another initial commit

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* another initial commit

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* one more initial commit

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* next step

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* next step

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* next step

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* next step

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* Refactored buffer() and shapeInfo() methods usage with NDArray class.

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* Adopt Graph class methods to use const shapes.

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* Adopt choose op to use constant shapes.

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* Adopt where op shape method to use constant shapes.

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* Adopt lstsq op to use constant empty shapes.

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* Adopt matrix_diag_part op shape routine to use constant shapes.

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* Adopt determinant ops to use constant shapes.

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* Adopt mean_pairwssqerr_loss ops to use constant shapes.

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* Adopt ops shape methods.

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* Adopt shape methods for loss ops.

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* Adopt log_loss op shape method.

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* Adopt shape methods for ops.

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* Adopt dilation2d ops shape methods.

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* Adopted deconv2d ops shape methods.

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* Adopted dynamicRNN op shape method.

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* Adopted shape methods for ops.

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* Adopted shape methods for lstm layer ops.

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* few updates

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* first cuda tweak

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* Adopt constant shapes for sconv2d ops.

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* Adopt constant shapes for gru ops.

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* Adopt constant shapes with shape methods for segment ops and so on.

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* Adopted constant shapes with unsorted_segment_* ops.

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* Adopted constant shapes with gamma op shape method.

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* Adopted shape methods of reduce_stddev ops.

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* Adopted shape methods for reduce_* ops.

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* Adopt shape method for squeeze op.

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* Adopt strided_slice shape method.

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* Refactored concat op shape method to adopt constant shapes.

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* Adopted shape method for mirror_pad op.

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* Adopted split op shape method.

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* Adopted tile ops shape methods.

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* Added const cast for mkldnn routines handles.

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* Refactored logSoftMaxForVector_ routine to conform with proper data and shape pointer casts.

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* Cosmetic changes to proper usage of constant pointers.

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* Refactored a couple shape comparators for strides and addBias helpers to proper use data pointers with inplace option.

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* Refactored depthToSpace helpers.

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* Refactored histogram helpers.

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* Refactored im2col helpers.

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* Refactored gather and gatherND helpers.

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* Fixed buffer usage on percentile helper.

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* Fixed gather shape with helpers and range buffer usage.

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* Fixed buffer usage with space to depth helpers.

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* Fixed buffer usage and constant shapes.

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* Fixed buffer usage with LUP decomposition>

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* Refactored onehot_ helper.

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* Refactored pad and prefix to use constant shapes.

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* Refactoed softmax helpers.

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* Fixed space to batch helpers to use buffers properly.

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* Fixed stack and split helpers.

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* Fixed buffer usage with sparse to dense helpers.

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* Fixed buffer usage with mindistance_ helpers.

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* Fixed buffer usage with tile helper.

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* Fixed constant shape usage.

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* Fixed constant shape usage with legacy pairwise bool ops.

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* Refactored a couple of methods to adopt constant shape usage.

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* Fixed broadcasting with constant shape."

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* Fixed const usage with inplace reverse and constant shapes with legacy reduction.

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* Refactored legacy ops with const shapes.

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* Refactored sort to adopt constant shapes.

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* Corrected sort for constant shape usage.

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* Fixed constant shape usage with special methods.

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* Refactored Context to conform with constant shape usage.

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* CUDA broadcasting headers

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* pairwise/indexreduce/random headers

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* Refactored native ops to adopt constant shapes.

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* legacy reduce3/scalar headers

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* Corrected pullRow signature and tests.

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* Corrected routines to proper use of constant shapes.

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* Refactored tests to use constant shapes properly.

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* Refactored legacy ops tests to use constant shapes properly.

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* Refactored buffer usage with NDArray tests.

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* Fixed native ops tests.

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* Fixed special concat routine.

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* Fixed buffer usage with test.

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* Fixed buffer usage with a test.

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* Refactored TAD.h and tests.

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* Refactored calcStrides* routines to use constant shapes.

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* Fixed miscelaneous errors with constant shapes.

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* NativeOps const changes

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* Corrected definitions for declared functions.

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* NativeOps const changes

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* few more const changes

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* Fixed const shapes with shape routines.

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* few more const changes

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* Fixed shape method for broadcastable case.

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* few more const changes

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* xw_plus_b BP shape fn restored

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* Fixed signatures with broadcasting.

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* Repaired backprops shape methods for a set of operations.

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* Refactored broadcast bool for cuda.

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* Refactored methods for 3 args with const qualifier.

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* Fixed a couple of kernel signatures for broadcasting.

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* Fixed kernels signatures for const buffers and shapes.

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* Refactored pairwise methods to persistent buffers and shapes usage.

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* Adopt const to buffers and shapes with kernels.

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* Adopt const to buffers and shapes with scalar kernels.

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* Refactored indexreduce kernels signatures to use const buffers and shapes.

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* Refactored pairwise kernels to adopt cons shapes and buffers.

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* Refactored pairwise bool kernels to adopt cons shapes and buffers.

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* Refactored random special ops to conform with const shapes and buffers.

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* Refactored native ops to conform with const shapes and buffers under cuda platform.

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* Cosmetical changes only.

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* Fixed const shapes and buffers error.

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* Corrected start pos routine.

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* Refactored methods to conform with const shapes and buffers.

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* Refactored helpers to use proper methods instead.

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* bunch of changes

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* next bunch of changes

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* next bunch of changes

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* Fixed execScalar declaration.

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* Fixed execScalar declaration.

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* Corrected const shape cases with sort and so on.

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* Fixed const shapes for sort.

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* Refactored kernel declarations to adopt const shapes.

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* Fixed kernels declarations to adopt const shapes.

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* Corrected kernel declarations to adopt const shapes and buffers.

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* Fixed kernels declarations to adopt const shapes.

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* Fixed segment helpers kernels declarations and so on to adopt const shapes.

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* Fixed const shape usage with segment and solve helpers.

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* Fixed kernel declaration with adjustWeight helper.

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* Fixed cuda implementations for constant shape helpers.

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* Adopted const shape usage with kernels.

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* Adopted top_k kernels to use const shapes and buffers.

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* Corrected kernels declarations to adopt const shapes with helpers.

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* Refactored NDArray definitions to adopt const shapes and buffers.

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* Fixed const shapes with image suppression helpers.

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* Slight improvement with buffers.

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* Refactored buffer usage.

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* Refactored buffer usage with tests.

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* Fixed const shape usage with definitions.

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* minor updates on cpu side

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* Refactored const shape usage with ConstantDescritor and native ops with cuda platform.

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* Refactored tear and tile kernels to adopt with const shapes.

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* softmax_loop fix

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* update missing signature

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* softmax again

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* few more missing consts

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* new methods updated

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Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-09 08:06:14 +03:00
raver119 0613485654
compression ops (#436)
* Added declarations for decode/encode_bitmap ops.

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* Added implementation for bitmap encoding/decoding ops.

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* Added helpers for encode/decode bitmap ops.

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* Refactored encodingBitmap helper.

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* threshold encode/decode skeleton

* helper skeleton

* minor import fix

* encoder shape fn & op impl

* thresholdEncode cpu impl

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* thresholdDecode cpu impl

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* Only cosmetical changes.

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* placeholder

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* Added cuda implementation for bitmap decode helper.

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* cuda thresholdEstimate

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* cuda thresholdDecode

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* next step

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* - nano cmakelist update (get rid of Clion section)
- fixed forgotten throw in AtomicTests

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* thesholdEncode cuda impl

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* Added tests for bitmap encoding/decoding ops.

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* Fixed tests for encode/decode bitmaps.

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* Refactored decode/encode helpers.

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* Fixed crashes with bitmap decode/encode helpers.

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* bitmap encode/decode CPU

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* bitmap encode/decode CUDA

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* C API removed for threshold/bitmap encode

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* EncodeBitmap/DecodeBitmap Java side

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* EncodeThreshold/DecodeThreshold Java side

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* EncodeThreshold/DecodeThreshold Java side

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* few more tests for threshold encoding

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* minor test tweak

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* two special tests

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* encodeBitmap CPU fix

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* parallel_long/parallel_double proper spans fix

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* encodeThreshold CUDA fix

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* nano fix

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* grid tweaks

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* RTX adaptation for thresholdEncode

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* don't allow threshold encoding for length < 2

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* get rid of NDArrayCompressor in EncodingHandler

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* one more minor update of EncodingHandler

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* one more minor tweak of EncodingHandler

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* - matmul allows integer data types use
- EncodingHandler boundary default value
- few tests for integer matmul

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* minor fix of CUDA bitmap encode

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* boundary changed to integer everywhere

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* boundary changed to integer everywhere

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* re-enable CUDA deallocator

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* threshold encoder fix for systems without omp

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* - encode_threshold now requires non-negative boundary
- minor tweak in EncodingHandler

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* restore parallelism in decode_bitmap

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* fall back to omp for encode_bitmap cpu

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* single time casts

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* - additional test for encode_threshold
- sync buffers to device before calling for shape function

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Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-08 20:59:39 +03:00
Yurii Shyrma 23e4aa99ad
Shyrma lstm layer bp (#370)
* - start working on bp for lstm

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* - further working on bp for lstmLayer

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* - minor change

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* - further work on bp for lstmLayer 2

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* - further work on bp for lstmLayer 3

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* - further work on bp for lstmLayer 4

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* - further work on bp for lstmLayer 5

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* - further work on bp for lstmLayer 6

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* - further work on bp for lstmLayer 7

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* - further work on bp for lstmLayer 8

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* - further work on bp for lstmLayer 9

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* - provide lstmLayerCell and lstmLayerCellBp as separate CUSTOM_OPs

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* - testing and fixing lstmLayerCellBp helper

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* - implement lstmLayerCellBp as separate op

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* - implement lstmLayerBp as separate op (not tested)

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* - fixing calculations of dLdWp and dLdb in lstmLayerCellBp

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* - further work on bp for lstmLayer 10

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* - fixing typo in lstmLayerTimeLoop

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* - forgot to perform clipping of c array and calculate corresponding derivative in lstmLayerCellBp

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* - further work on bp for lstmLayer 10

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* - testing and fixing bugs in lstmLayer_bp op 1

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* - testing and fixing bugs in lstmLayer_bp op 2

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* - turn off heavy tests for cuda for lstmLayer_bp op

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* - forgot to nullify gradients at eliminated time steps (when sequnce length array is present )

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2020-04-13 13:21:51 +03:00
Yurii Shyrma e42b4e96c3
correct output empty shapes deducing in split op (#311)
* - correct output empty shapes deducing in split op

Signed-off-by: Yurii <iuriish@yahoo.com>

* java test fixed

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* - split broadcast::exec function on individual functions corresponding to switch arg

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* - split broadcast::exec _int and _bool function on individual functions corresponding to switch arg

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Co-authored-by: raver119 <raver119@gmail.com>
2020-03-12 18:25:54 +03:00
raver119 88f39fad67 pairwise compilation units updated
Signed-off-by: raver119 <raver119@gmail.com>
2020-03-12 12:50:09 +03:00
Yurii Shyrma ebab6b6410
Shyrma broadcast2 (#309)
* - profiling broadcast ops for aurora

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* - correct loop limit type in shape::haveSameShapeAndStrides

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2020-03-11 17:58:53 +03:00
Yurii Shyrma 58550b7c98
[WIP] Shyrma coords (#305)
* - provide faster index2coords function for cpu

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* - new faster index2coords function is introduced into cpu code

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* - replace long long coordinates with int coordinates

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* - add missed reload of coords2index function

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* - reststart  jenkins

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* - rollback changes in convolutions.cu and addBias.cu

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2020-03-11 16:21:59 +03:00
raver119 50b7d82b96 more compilation units
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2020-03-11 11:43:18 +03:00
Yurii Shyrma 6aaca58506
Shyrma broadcast (#302)
* - profiling TrueBroadcastHelper

Signed-off-by: Yurii <iuriish@yahoo.com>

* - further improving of TrueBroadcastHelper

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* - further profiling of broadcast op

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* - implementation of broadcastShapeHelper which inserts unities in shapes of arrays to be broadcasted

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* - provide additional method in ConstantShapeHelper class for deducing broadcast shapes with unities

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* - provide new NativeOps helpers for usual and true broadcast methods

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* enable bert profiler

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* - delete unnessesary tests

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2020-03-10 16:29:09 +03:00
raver119 57210b936c
Revert "OpenMP Threads execution (#297)" (#299)
This reverts commit dd2043ef48.
2020-03-09 08:22:49 +03:00
raver119 dd2043ef48
OpenMP Threads execution (#297)
* omp threads backported

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* omp scalar reduce

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* timing

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* timing

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* minor tweaks

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* minor tweaks

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* namespace change

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* num_threads

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* one minor fix

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2020-03-09 08:21:44 +03:00
raver119 63fa3c2ef3
libnd4j polishing (#273)
* 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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2020-03-02 12:49:41 +03:00
Oleh b4575d11e9
Loops auto-vectorization problem fix (#274)
* libnd4j cast loop types

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j more type castination added to loops

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j sync casting types of iterated variable in loops

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j more loops reviewed for vectorization problem fix

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j fixed several typos

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j several more files reviewed to fix auto-vectorization problem in loops

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j merge master and reviewed more files to fix auto-vectorization problem in loops

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j several type casting added in broadcasting that were missed, fixed mac builds

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j double check all files and fix several more places in loops

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j fixed builds

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* libnd4j revert changes for lup.cpp

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2020-02-26 21:12:19 +03:00
raver119 e78be14cc1
arm fix (#260)
* range check for scalar_int

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* no simd

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* no ops

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* cyclic shift?

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* left split

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* left split

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* rot ops unrolled templates

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* no rotl/rotr for uint64

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* no rotl/rotr for uint64 2

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* no rotl/rotr for uint64 3

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* ARM_BUILD declared

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2020-02-21 14:31:00 +03:00
Oleh 0748c7e7c2
Oleh broadcast4d (#257)
* libnd4j raw implementation of native broadcast for special cases

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j fixed bugs for special case of 4D loop broadcast, add some tests, need more testing and discussion

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j added 3D and 5D cases support and tests, need testing with different orders

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* libnd4j correctd case selection for broadcast 3,4,5D loops, fixed several places for more stable behavior, clean up

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* libnd4j minor corrections to avoid some risks in strides selection, added tests and rename some variables

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* libnd4j optimize usage the stride selection for all loops in separate ShapeUtils method copyCertainStridesFromShapeInfo, merge master

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* libnd4j remove per request several tests for 3D, 4D and 5D broadcast loops

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* libnd4j removed some loac changes that had not been sync with serve playground, turn on new loops usage
2020-02-21 07:46:05 +03:00
raver119 215641ea9e
Minor improvements (#255)
* static increments in loops

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* specials and concat split into separate units

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2020-02-20 11:43:26 +03:00
raver119 2698fbf541
Broadcast perf improvements (#248)
* broadcast as scalar edge case

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* missing return

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* few fixes

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* one more fix

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* no need for lambdas

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2020-02-17 16:25:09 +03:00
Oleh 6e6289b6b9
Oleh bert multiply true broad cast (#239)
* libnd4j trueBroadcast rank 3 row implementation of special case

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j rule clarify for second special case for all tests pass

* libnd4j parallel_tad loop switch on in special case

* libnd4j more general case for special case 2, need additional testing

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j more general case for trueBroadcast special cases added

* libnd4j minor corrections and clean up

* libnd4j one more minor fix

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j fixed check point to support all Y common vector representations in first special case for trueBroadcast

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

Co-authored-by: raver119 <raver119@gmail.com>
2020-02-14 12:04:38 +03:00
Yurii Shyrma fe47f52896
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with  master

* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* Libnd4j: TensorMMul backprop op #8174 sync master

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)

Signed-off-by: Yurii <iuriish@yahoo.com>

* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot

Signed-off-by: Yurii <iuriish@yahoo.com>

* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure

Signed-off-by: Yurii <iuriish@yahoo.com>

* - further work on problem of wrong shape evaluation during permute/reshape procedures

Signed-off-by: Yurii <iuriish@yahoo.com>

* - still looking for bug reason in reshape/permute stuff

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correct bug in transform cuda native ops

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correct bug in NDArray::assign

Signed-off-by: Yurii <iuriish@yahoo.com>

* - remove old shape::reshape stuff

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* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class

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* - correct bug in tensorDot which had to do with wrong pointers assigments

Signed-off-by: Yurii <iuriish@yahoo.com>

Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 20:33:54 +03:00
Oleh 11cb561045
Oleh true broadcast opt (#234)
* libnd4j trueBroadcast special case

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j fix trueBroadcast special case

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j special case of TrueBroadcastHelper

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* libnd4j trueBroadCast special case and test

* libnd4j minor changes sync with master

* libnd4j changes to TrueBroadcastHelper.hpp per require

Signed-off-by: Oleg <oleg.semeniv@gmail.com>
2020-02-12 14:12:17 +03:00
raver119 237c137166 few more smaller compilation units (#226)
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2020-02-10 10:57:18 +03:00
raver119 8a0d5e3b97
Compilation units (#224)
* - TrueBroadcastHelper split into multiple compilation units
- legacy gemm.cpp disabled

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* - IndexReduce int32/int64 split into multiple compilation units

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* - Reduce3 ops split into multiple compilation units

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2020-02-09 19:48:32 +03:00
Abdelrauf d39ca6d488
ElementWiseStride==1 cases for legacy random ops (#202)
Signed-off-by: AbdelRauf <rauf@konduit.ai>
2020-01-31 08:57:31 +03:00
raver119 7783012f39
cuDNN integration (#150)
* 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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2020-01-20 21:32:46 +03:00
Oleh 8fc0e63ce7 Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation

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* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps

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* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops

* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar

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* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests

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* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated

* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast

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* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing

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* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review

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* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up

* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar

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* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests

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* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up

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* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization

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* pow_bp wrapper

* Fixed PowBp wrapper

* Tests added

* Test fixed

* Fix return type

* Disable powBp usage

* Pow backprop changed

Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 12:59:12 +03:00
raver119 29e8e09db6
String changes (#3)
* initial commit

* additional data types & tensor type

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* next step

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* missing include

* sparse_to_dense

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* few more tests files

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* draft

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* numeric sparse_to_dense

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* comment

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* string sparse_to_dense version

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* CUDA DataBuffer expand

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* few tweaks for CUDA build

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* shape fn for string_split

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* one more comment

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* string_split indices

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* next step

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* test passes

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* few rearrangements for databuffer implementations

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* add native DataBuffer to Nd4j presets

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* DataBuffer creation

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* use DataBuffer for allocation

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* cpu databuffer as deallocatable

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* DataBuffer setters for bufers

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* couple of wrappers

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* DataBuffers being passed around

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* Bunch of ByteBuffer-related signatures gone

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* - few more Nd4j signatures removed
- minor fix for bfloat16

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* nullptr pointer is still a pointer, but 0 as address :)

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* one special test

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* empty string array init

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* one more test in cpp

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* memcpy instead of databuffer swap

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* special InteropDataBuffer for front-end languages

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* few tweaks for java

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* pointer/indexer actualization

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* CustomOp returns list for inputArumgents and outputArguments instead of array

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* redundant call

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* print_variable op

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* - view handling (but wrong one)
- print_variable java wrapper

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* one more test

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* - empty arrays handling

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* - deserialization works now

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* minor fix

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* meh

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* one more fix

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* initial cuda commit

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* print_variable message validation

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* CUDA views

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* CUDA special buffer size

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* minor update to match master changes

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* - consider arrays always actual on device for CUDA
- additional PrintVariable constructor
- CudaUtf8Buffer now allocates host buffer by default

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* meh

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* - print_variable now allows print from device

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* InteropDataBuffer data type fix

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* ...

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* disable some debug messages

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* master pulled in

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* couple of new methods for DataBuffer interop

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* java side

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* offsetted constructor

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* new CUDA deallocator

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* CUDA backend torn apart

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* CUDA backend torn apart 2

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* CUDA backend torn apart 3

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* - few new tests
- few new methods for DataBuffer management

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* few more tests + few more tweaks

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* two failing tests

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* one more test

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* two failing tests pass

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* now we pass DataBuffer to legacy ops too

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* Native DataBuffer for legacy ops, Java side

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* CPU java side update

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* CUDA java side update

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* no more prepare/register action on java side

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* NDArray::prepare/register use now accepts vectors

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* InteropDataBuffer now has few more convenience methods

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* java bindings update

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* tick device in NativeOps

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* Corrected usage of OpaqueBuffer for tests.

* Corrected usage of OpaqueBuffer for java tests.

* NativeOpsTests fixes.

* print_variable now returns scalar

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* one more test

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* compat_string_split fix for CUDA

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* - CUDA execScalar fix
- CUDA lazyAllocateHostPointer now checks java indexer/pointer instead of native pointer

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* legacy ops DataBuffer migration prototype

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* ignore device shapeinfo coming from java

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* minor fix

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* minor transformAny fix

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* minor tweak for lazy host allocation

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* - DataBuffer::memcpy method
- bitcast now uses memcpy

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* - IndexReduce CUDA dimension buffer fix

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* views for CPU and CUDA

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* less spam

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* optional memory init

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* async memset

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* - SummaryStats CUDA fix
- DataBuffer.sameUnderlyingData() impl
- execBroadcast fix

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* - reduce3All fix
switch to CUDA 10 temporarily

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* CUDA version

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* proper memory deallocator registration

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* HOST_ONLY workspace allocation

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* temp commit

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* few conflicts resolved

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* few minor fixes

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* one more minor fix

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* NDArray permute should operate on JVM primitives

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* - create InteropDataBuffer for shapes as well
- update pointers after view creation in Java

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* - addressPointer temporary moved to C++

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* CUDA: don't account offset twice

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* CUDA: DataBuffer pointer constructor updated

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* CUDA NDArray.unsafeDuplication() simplified

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* CUDA minor workspace-related fixes

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* CPU DataBuffer.reallocate()

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* print_affinity op

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* print_affinity java side

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* CUDA more tweaks for data locality

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* - compat_string_split tweak
- CudaUtf8Buffer update

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* INDArray.close() mechanic restored

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* one more test fixed

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* - CUDA DataBuffer.reallocate() updated
- cudaMemcpy (synchronous) restored

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* one last fix

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* bad import removed

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* another small fix

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* one special test

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* fix bad databuffer size

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* release primaryBuffer on replace

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* higher timeout

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* disable timeouts

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* dbCreateView now validates offset and length of a view

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* additional validation for dbExpand

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* restore timeout back again

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* smaller distribution for rng test to prevent timeouts

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* CUDA DataBuffer::memcpy now copies to device all the time

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* OpaqueDataBuffer now contains all required methods for interop

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* some javadoc

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* GC on failed allocations

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* minoe memcpu tweak

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* one more bitcast test

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* - NDArray::deviceId() propagation
- special multi-threaded test for data locality checks

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* DataBuffer additional syncStream

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* DataBuffer additional syncStream

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* one ignored test

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* skip host alloc for empty arrays

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* ByteBuffer support is back

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* DataBuffer::memcpy minor fix

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* few minor prelu/bp tweaks

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* nullify-related fixes

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* PReLU fixes (#157)

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* Build fixed

* Fix tests

* one more ByteBuffer signature restored

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* nd4j-jdbc-hsql profiles fix

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* nd4j-jdbc-hsql profiles fix

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* PReLU weight init fix

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* Small PReLU fix

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* - INDArray.migrate() reactivated
- DataBuffer::setDeviceId(...) added
- InteropDataBuffer Z syncToDevice added for views

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* missed file

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* Small tweak

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* cuda 10.2

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* minor fix

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Co-authored-by: shugeo <sgazeos@gmail.com>
Co-authored-by: Alex Black <blacka101@gmail.com>
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-04 13:27:50 +03:00
Yurii Shyrma 5d9b2a16e5 Shyrma temp (#131)
* - 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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2019-12-20 22:35:39 +03:00
raver119 bd4f77c652 Compilation units (#124)
* IndexReduce and Reduce3 split into few units

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* IndexReductionLoops split as well

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* reduce_float split as well

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2019-12-14 21:59:37 +02:00
raver119 a5f5ac72b1
reduce bool changes (#118)
* reduce bool changes

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* reduce bool tweaks

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2019-12-09 20:08:59 +03:00
Yurii Shyrma 1f5e15b541 Shyrma adjust (#98)
* - 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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2019-12-03 09:40:45 +03:00
raver119 064a56ccf1
Few fixes (#66)
* skip legacy transforms execution in case of empty input arrays

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* - BroadcastBool ops now accept extraParams to make MatchCondition possible
- TrueBroadcastHelper now uses samediff::threads

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* java side

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* trigger jenkins

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* update LessThanOrEqual opNum mapping

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* update LessThanOrEqual opNum mapping

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2019-11-21 15:43:03 +03:00
raver119 db7ca956c5
[WIP] Mish (#55)
* Mish activation function and its derivative

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* signature fix

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* mish as activation for dl4j

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* javadoc

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* minor optimization

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2019-11-18 13:21:26 +03:00
raver119 6de00bf75f
[WIP] Weekly update of repo (#8390)
* [WIP] Fix compilation after nd4j changes (#37)

* Fix compilation.

* Some tests fixed

* Disable tests temporarily.

* Restored test

* Tests restored.

* Test restored.

* [WIP] perf tests (#40)

* special maxpool test

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* special maxpool test

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* Shyrma bnorm bp (#41)

Batchnorm backprop mkldnn

* Add SameDiff memory reuse memory manager (array cache) (#39)

* Attention op comments

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* ArrayCacheMemoryMgr - first pass

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* Tweak array cache for use with SameDiff identity arrays

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* ArrayCacheMemoryMgr javadoc and properly get max memory

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* LRU cache policy + add tests

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* Fixes

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* Resize arrays internally if required for ArrayCacheMemoryMgr

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* Test improvement

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* Small polish

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* SameDiff op runtime benchmarking listener (#42)

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* INLINE_LOOPS for windows

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* [WIP] ThreadPool (#8)

This PR removes OpenMP use in 95% of cases
2019-11-13 17:15:18 +03:00
shugeo 7b14a9f603
Gamma and Poisson distributions (#27)
* Added implementation for random_gamma op.

* Added implementation for random_poisson op and support classes.

* Added helpers for random_poisson and random_gamma ops.

* Implementation of random_poisson. The first working edition.

* Implementation of random_poisson. Parallelized working edition.

* Implementation of random_gamma. Parallelized working edition with alpha only.

* Added cuda implementation for helper of poisson distribution.

* Corrected shape calculation with random_gamma and tests.

* Finished cpu implementation for gamma distribution.

* Finished cuda implementation for random_gamma op.

* Refactored cpu helpers for random_gamma and random_poisson ops.

* Refactored cuda helpers for gamma and poisson distribution.

* Refactored cuda helper for gamma distribution.

* Refactored cpu helper for random_poisson op.

* Refactored cpu helper for random_gamma op.
2019-11-04 15:42:28 +02:00
Yurii 70bd925abd - write 2 versions of new lstmLayer: one is based on own code, second uses mkl dnn api 2019-10-17 20:44:52 +03:00
shugeo 7103aca8c5 Added broadcastable IGamma and IGammac ops. 2019-10-16 13:58:32 +03:00
shugeo 908e4c4912 Added implementation for divide_no_nan op and tests. 2019-10-04 10:29:15 +03:00
raver119 cff26f13c5
Revert "Implement divide_no_nan op." 2019-10-03 20:25:52 +03:00
shugeo 6eaca179d6 Implement divide_no_nan op. 2019-10-03 18:22:17 +03:00
shugeo e1a7460f8e Shugeo cuda doc2 (#255)
* Added comments to tileKernel routine.

* Refactored kernel and added doc to it.

* Refactored setDiagonal kernel and added doc for it.

* Added doc for tnse cuda helpers.

* Added doc for diag kernels.

* Added doc for kernel.

* Refactored code with fake quantization.

* Added docs for image resize and crop kernels.

* Added docs for image suppression helpers.

* Added docs to matrix_band helpers.

* Added docs for matrix_diag_part and nth_element helpers.

* Fixed syntax error and refactored getIndexOffset usage.
2019-09-11 21:04:43 +03:00
raver119 589401477d
[WIP] bunch of improvements (#257)
* - 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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2019-09-11 20:12:09 +03:00
raver119 106524663b fix double consumption of rng on cpu
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2019-09-02 15:24:51 +03:00
raver119 e42c34ca55
[WIP] minor (#218)
* - initial docs commit
- merge* cuda fix

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* one more fix

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* one more fix

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2019-09-02 11:25:48 +03:00
Yurii Shyrma a35926c6e9 - add parameter alpha to elu and lrelu_bp (#213)
* - add parameter alpha to elu and lrelu_bp

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* - forgot to correct header activations.h

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2019-08-31 20:57:39 +03:00
raver119 1003428a18
[WIP] Int broadcastables (#195)
* Removed invalid resource and fixed tests

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* legacy scalar/pairwise/broadcast int ops

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* NDArray int broadcastables

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* few more bitwise tests

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* java side update

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* Argument type changed for shift ops

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* legacy scalar/pairwise/broadcast int ops

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* NDArray int broadcastables

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* few more bitwise tests

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* java side update

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* Argument type changed for shift ops

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2019-08-30 10:12:40 +03:00
raver119 df84bc7255
[WIP] More tweaks (#173)
* 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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2019-08-27 10:37:10 +03:00