Commit Graph

15 Commits (e7a995e959d4bb7dc196d08953ec7ea8081fed56)

Author SHA1 Message Date
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
shugeo 1bb3ae4b03
Shugeo unordered map (#256)
* Refactored usage of std::map to std::unordered_map instead.

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* Eliminated crash with wrong ShapeDescriptor hash.

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* Eliminated crash with TadDescriptor hash.

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* Refactored Stash hash.

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* Refactored hashes.

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* Refactored TadDescriptor hash and top_k mapping.

* Refactored hashes for ShapeDescriptor and TadDescriptor classes.

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* Refactored hash for ConstantDescriptor and ShapeDescriptor classes.

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* Fixed map using with cuda platform.

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* - few rearrangements for hash functions
- shared openblas allowed

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* exports

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* exports

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* Stash reverted to std::map

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* Added additional test.

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* different maps for different compilers

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* missing include

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* fix the leak

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2020-02-24 07:51:01 +03:00
Abdelrauf f25056363b auto-vectorization check for gcc (#172)
* Autovectorization tool:
- sync output for gnu make
- Reduced html output
- links for line numbers
- AutoVectorization.md
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* Detailed report with `-fsave-optimization-record` option
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* Readme

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2020-01-28 19:00:12 +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
raver119 fdda0221ed
[WIP] CUDA build (#109)
* working prototype of new CUDA build with cmake

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* get rid of older stuff

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* remove legacy CUDA debug section

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* fPIC for GCC

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* - switch to /MD
- make MSVC runtime lib configurable from 1 place

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* few last tweaks

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* mae static library optional

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* typo fixed

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2019-12-14 14:38:17 +03:00
raver119 25b3cd9b80
[WIP] CUDA tests (#95)
* one more CI test

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* export additional symbols

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* few more tweaks

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* one more tweak for linux

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* fix dtype in few tests

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* missing sync and memset in couple of tests

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* copy step for libnd4j cuda

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* no-op on empty for adjust hue/contrast/saturation

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* CUDA_VERBOSE Off

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* BroadcastBool fix + few tests

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* trigger jenkins

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* trigger jenkins

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* - ignore couple of warnings
- remove redundant compiler options

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2019-12-02 21:37:21 +03:00
raver119 59e955cedc
- MKL-DNN version upgrade to 1.1.x (#62)
- MKL-DNN namespace changes to match DNNL rename

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2019-11-20 13:23:08 +03:00
Alex Black 09a827fb6d
Fixes and pre-release QA (#51)
* #8395 Keras import - support scaled identity weight init

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* More Keras scaled weight init fixes

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* #8352 Deprecate duplicate SamplingDataSetIterator class

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* Remove /O2 optimization for faster CUDA build

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* Tweak regression test precision for CUDA

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* Fix edge cases for buffer creation

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* Update MKLDNN validation tests to new helper enable/disable settings

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* Delete debugging class

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* MKLDNN test - add proper skip for CUDA backend

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* Align WeightInitUtil with weight init classes

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* Fix for SameDiff test layers weight init when using IWeightInit classes

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2019-11-16 17:04:29 +11:00
raver119 48df1acdfb
[WIP] ThreadPool (#8)
This PR removes OpenMP use in 95% of cases
2019-11-13 17:04:59 +03:00
raver119 f05c6ee139 INLINE_LOOPS for windows
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2019-11-12 15:12:31 +03:00
Yurii Shyrma 0cdb5750e0
Shyrma concat (#24)
* - provide possibility to pass axis as last input array in concat op
- corrcect sumation in bias_add_bp op for NHWC case

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* - write code for deconv2d op based on mkl dnn api

* no unsafe math

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* no unsafe math

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* - get rid of e<> and p<> methods in svd helper

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* - provide mkl api support for deconvolution 3d

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* - write deconv2d_bp based on mkl api

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* - write deconv3d_bp based on mkl api

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* - testing and fixing deconv based on mkl api

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* - remove dilation form conv2d/3d mkl

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* - minor changes

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* - further corrections of deconv ops based on mkl dnn api

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* - provide deconv2d_tf based on mkl dnn api

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* - add minor corrections required by reviewer

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2019-11-03 12:37:19 +02:00
raver119 98e2814879
Platform helpers (#8216)
* platform helpers draft

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* typo

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* disable platform cmake

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* another draft

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* mkldnn convolution refactored

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* minor tweaks

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* one more safety check

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* prototype works

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* meh

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* force static library mode for mkldnn

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* - ismax fix
- experimental arg fix
- don't enforce openblas on Apple hardware

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* bunch of small fixes

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* declare concurrent

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* - MKLDNN version upgrade to 1.0.2
- avgpool2d/maxpool2d APIs update

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* - avgpool2d_bp/maxpool2d_bp APIs update

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* - conv2d/batchnorm APIs update

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* - lrn/conv2d_bp/conv3d/conv3d_bp APIs update

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* all ops converted to MKLDNN 1.x

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* bunch of tweaks

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* namespace for platform helpers

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* make sure platform helpers aren't opimized out

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* build cpu_features on x86 systems

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* build cpu_features on x86 systems

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* more of cpu_features

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* - mkldnn removed from java
- cpu_features checks in CpuNDArrayFactory

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* F16C definition renamed

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* some mkldnn rearrangements

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* check supported instructions before doing anything

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* typo

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* missied impl

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* BUILD_PIC option

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* conv2d fix

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* avgpool3d fix

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* avgpool3d_bp fix

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* avgpool2d_bp leak fix

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* avgpool3d_bp leak fix

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* maxpool bp leaks fixed

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* printf removed

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* batchnorm fix

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* AVX warning/error polishing

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* Fix

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* More polish

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* Polish

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* remove previous MKL-DNN support layer

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* avx2 tweak

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* allow static for apple

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* exclude mkldnn in one more place

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* exclude mkldnn in one more place

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* restore OPENBLAS_PATH use

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* add runtime check for avx/avx2 support

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* convolution_auto

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* Add logic for helper argument

* minor test fix

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* few tweaks

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* few tweaks

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* skip OpTracker props for non-x86 builds

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* linux arm isn't x86 :)

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* avx-512

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* CUDA presets fix

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* BUILD_PIC

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* prefetchw for avx2

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* BUILD_PIC again

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2019-09-11 21:50:28 +03:00
skymindops b5f0ec072f Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00