Commit Graph

16 Commits (4f98c716ee4b436f106da1ee12310ac14bb6204e)

Author SHA1 Message Date
agibsonccc 6dc7e2f08f Update c++ copyrights 2021-02-01 21:31:45 +09:00
Yurii Shyrma 76f3553679
Shyrma merge max ind (#443)
* - provide correct possible output types in mergeMaxIndex op

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

* - cleaning up the unneeded backprop arg in reverse_bp op

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

* - improve clipByNorm both ff and bp

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* - implementation and testing clipByAvgNorm_bp op

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* - pass biases in any way in dnnl lstm op, they are zeros when user doesn't provide them to us

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

* - start working on mkldnn concat op

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* - further work on mkldnn concat

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* missing declaration fix

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* - polishing mkl ops

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* - testing and fixing bugs in mkl concat op

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* - fix linkage error for windows cuda build

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* - further conflicts resolving with master

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* - fix format tags in mkldnn matmul op

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* - provide additional type cast in clip.cu

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* - finally bug in mkldnn tanh_bp was caught

Co-authored-by: raver119@gmail.com <raver119@gmail.com>
2020-05-12 07:47:09 +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.

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

* 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
Yurii Shyrma e700b59f80
Shyrma weights format (#329)
* - start to introduce additional weights formats into conv2d ops

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

* - provide weights format variety in backprop conv2d and deconv2d ops, testing and fixing bugs

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* - forgot to recover kernels sizes in deconv2d_bp test

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* - built in weights format in depthwise conv 2d op

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* - provide new weights formats in mkl dnn conv ops

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* - provide new weights formats in cuda conv helpers

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* - working with new weights format in cudnn conv api

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* - take into account order of arrays in cudnn tensor descriptions

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* - provide new weights formats in cpu conv3d (ff/bp)

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* - provide new weights formats in cpu deconv3d (ff/bp)

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* - provide new weights formats in conv3d ops (ff/bp) based on mkl api

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* - provide new weights formats in conv3d ops (ff/bp) based on cudnn api

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* - resolve conflicts 2

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Co-authored-by: raver119 <raver119@gmail.com>
2020-03-20 12:11:27 +03:00
raver119 7a2ac800dd
Nullify (#304)
* initial commit

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* bunch of tweaks

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* hamming distance nullification

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* Add output array value assignment for testing/debugging

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* don't assign empty arrays

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* conv2d/conv3d/depthwise2d nullified

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* conv2d/conv3d/depthwise2d nullified

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* conv2d/conv3d/depthwise2d nullified

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* few more fixes

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* im2col

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* pooling?

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* more nullified

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* ismax nullified

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* rollback ismax nullification

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* synchronized cublas handle use on per-device basis

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* hiding method from jcpp

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* get rid of test assigns in DeclarableOp

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* get rid of assigns

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* proper deviceId is back

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* include fixed

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Co-authored-by: Alex Black <blacka101@gmail.com>
2020-03-20 08:49:28 +03:00
Oleh 41bde8f885
Softmax BP mkldnn implementation (#301)
* libnd4j mkldnn softmax_bp operation implementation and integration, 2 tests added, need some refactoring and code clean up and more testing with different input shapes

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

* libnd4j softmax_bp update, code refactoring, etc

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

* libnd4j merge master, fixed typos, minor tweaks, code clean up

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

* libnd4j  integrate mkldnnUtils helpers in other mkldnn operations

Signed-off-by: Oleg <oleg.semeniv@gmail.com>
2020-03-12 18:25:29 +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
Yurii Shyrma 948646b32d
Shyrma mkl test (#211)
* - provide nhwc format in mkl conv ops

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* - corrections in mkl conv3d

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* - corrections in mkl batchnorm

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* - corrections in mkl maxpooling2d

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* - add format format_tag::any to outputs in mkl conv ops

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* - complete corrections in mkl conv ops

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* - add test for comparison of execution speeds of mkl conv2d op with different weights format

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* - take into account order f in mkl conv ops

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2020-02-06 21:12:54 +03:00
raver119 5d28e6143d
OpContext handling (#214)
* nano tweaks

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* OpContext tweaks

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* OpContext deallocators

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* get rid of few mkldnn safety checks

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* databuffer setSpecial fix

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2020-02-05 07:27:24 +03:00
Yurii Shyrma 7a7ee4b021 Shyrma cudnn (#192)
* - implementation of cudnn batchnorm_bp op

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* - testing and fixing bugs in batchnorm_bp based on cudnn api

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* - move pooling mkl code and delete some unnecessary files

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* - implementation and testing cudnn pooling2d ops (avg/max, ff/bp)

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* - implementation and testing cudnn pooling 3d (ff/bp) ops

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* - provide ff step in case of cudnn maxpool3d_bp op

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* - remove half type from set of supported types in mkl dpethwise conv op

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* - bring back cudaStreamSynchronize in batchnorm and pooling cudnn ops

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Co-authored-by: raver119 <raver119@gmail.com>
2020-01-28 18:23:07 +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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Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 21:32:46 +03:00
raver119 cb18d3d996
allow MKL-DNN on non-AVX machines (#104)
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2019-12-04 09:11:37 +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
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
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