* init in this branch
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* Lenetet Mnist workflow
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* small fix for calculations
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* for Alex to check placeholder null pointer issue
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* CNN3D workflow
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* state for launching on dxg to regenterate dl4j examples
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* SD RNN test case workflow
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* small fixes
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* checkpoint at lstmBlock: Input array 1 (x) rank must be got input with rank 2 issue
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* Fix LSTMLayer inputs order
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* lstm mismatch with c++ op issue
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* LSTMLayer config draft
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* LSTMLayer config draft v2
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* have doubt I had to do this
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* NDRNN generated by codegen
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* LSTMLayerTestCases draft
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* minor fixes again
* added LSTMLayer testcases to nd4j-tests + setted Preconditions in LSTMLayer constructors
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* added lost SDCNNtestcases
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* overrided getNumOutputs from DynamicCustomOp in LSTMLayer and reorganized LSTMLayerOutputs according to cpp op
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* finished with LSTMLayerOutputs
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* Fix MKLDNN platform checks (i.e., when MKLDNN can be used vs. not)
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* Fix LSTMLayerWeights input order
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* More fixes
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* minor fixes
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* fixed LSTMLayer testcases
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* finished SameDiffRNNTestCase
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* finished all testcases + minor fixes
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* Multiple generation-related fixes
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* Fix multiple issues
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* More fixes
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* LSTM fixes
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* Regenerate ND4J namespaces and fix multiple issues
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* changed SameDiffRNNTestCase
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* Small fix
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* added Nd4j.getRandom().setSeed(12345) where needed
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* #8828 Fix ND4J profiler NaN/Inf checks when using OpContext
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* #8828 Fix ND4J profiler NaN/Inf checks when using OpContext
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* Tweak to weight init for SameDiff CNN test case
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* Tweaks for test cases
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* Ignore failing tests until fixed
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* Fix
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Co-authored-by: Alex Black <blacka101@gmail.com>
* - 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>
* 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
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* libnd4j merge master, fixed typos, minor tweaks, code clean up
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* libnd4j integrate mkldnnUtils helpers in other mkldnn operations
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* 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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* 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
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
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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
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
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* - 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
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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>
* 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
Signed-off-by: Yurii <iuriish@yahoo.com>
* - implementation of conv2d backprop op based on cudnn api
Signed-off-by: Yurii <iuriish@yahoo.com>
* - 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>
* - 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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* - write code for new batchnorm backprop
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* - testing batchnorm backprop
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* - write code for batchnorm backprop based on mkl dnn api
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* - testing and fixing bugs in batchnorm_bp mkl dnn
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* - made corrections required by reviewer
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* - change name in java wrapper for batchnorm op
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raver119
Andrii T
Yurii Shyrma
Oleh