Commit Graph

11 Commits (a609517d3cb41b39779f07e878af7f0f10b439df)

Author SHA1 Message Date
agibsonccc 46dbd0b203 Update copyrights remove attic and relocate elsewhere 2021-02-09 13:16:31 +09:00
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
Yurii Shyrma e700b59f80
Shyrma weights format (#329)
* - start to introduce additional weights formats into conv2d ops

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* - 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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2020-03-20 12:11:27 +03:00
Yurii Shyrma 78934c17ad
profiling of stack and unstack ops (#261)
* - profiling of stack and unstack ops

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* - fix bug in cpu concat op

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* - correction of cuda stack and unstack

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* - change shape.h method which operates with unity dimensions strides

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* - rearrange stack tests

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* - correct evaluation of smallest stride for moving through contiguous axis

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* - forgot to update signature of function strideOverContigAxis in cuda concat and split ops

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* - remove ShapeUtils::shapeAsString method applied before input arrays validations

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* -  further removing of ShapeUtils::shapeAsString

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* - take sub-array shapeIndo/offset calculation out of NDArray class
- add possibility of contiguous memory copy in execTransformAny op if opNum == assign

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* - correct test_empty_scatter_2 in EmptyTests.cpp

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* - profiling of slice op

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* - get rid of contiguous memcpy for some cases in concat and split ops

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* - forgot to declare oid nd4j::SpecialMethods<T>::splitCpuGeneric

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* - correct typo in calculation of threads in cuda split op

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* - forgot to correct another set of threads variables in split cuda ops

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* - further conflicts resolving

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2020-03-03 07:32:37 +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 fe47f52896
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation

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

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

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

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

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

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

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* 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

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

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* 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

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* 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

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* Libnd4j: TensorMMul backprop op #8174 sync master

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

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

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

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

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

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

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* - correct bug in transform cuda native ops

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* - correct bug in NDArray::assign

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* - 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

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Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 20:33:54 +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
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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Co-authored-by: raver119 <raver119@gmail.com>
2019-12-20 22:35:39 +03:00
Yurii Shyrma d19eeaec52 Shyrma casual conv1d (#90)
* - add causal mode of padding to convolutions

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* - add additional tests for causal conv1d

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* - add causal mode for cuda conv kernels

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* Java side of Conv1D changes

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* Add Conv1DDerivative op

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* Causal Conv1D gradient checks

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* Tweaks

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* - add causal padding mode to conv2d_bp

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* More thorough causal conv1d tests

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2019-11-29 14:14:30 +03:00
AlexDBlack a66e03355e Merge remote-tracking branch 'fork/master' 2019-09-12 12:20:57 +10:00
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