* 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 cast loop types
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* libnd4j more type castination added to loops
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* libnd4j sync casting types of iterated variable in loops
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* libnd4j more loops reviewed for vectorization problem fix
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* libnd4j fixed several typos
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* libnd4j several more files reviewed to fix auto-vectorization problem in loops
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* libnd4j merge master and reviewed more files to fix auto-vectorization problem in loops
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* libnd4j several type casting added in broadcasting that were missed, fixed mac builds
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* libnd4j double check all files and fix several more places in loops
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* libnd4j fixed builds
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* libnd4j revert changes for lup.cpp
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* static increments in loops
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* specials and concat split into separate units
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* initial commit
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* - gruCell_bp further
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* - further work on gruCell_bp
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* Inverse matrix cublas implementation. Partial working revision.
* Separation of segment ops helpers. Max separation.
* Separated segment_min ops.
* Separation of segment_mean/sum/prod/sqrtN ops heleprs.
* Fixed diagonal processing with LUP decomposition.
* Modified inversion approach using current state of LU decomposition.
* Implementation of matrix_inverse op with cuda kernels. Working revision.
* Implemented sequence_mask cuda helper. Eliminated waste printf with matrix_inverse implementation. Added proper tests.
* - further work on gruCell_bp (ff/cuda)
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* comment one test for gruCell_bp
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* - provide cuda static_rnn
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* Refactored random_shuffle op to use new random generator.
* Refactored random_shuffle op helper.
* Fixed debug tests with random ops tests.
* Implement random_shuffle op cuda kernel helper and tests.
* - provide cuda scatter_update
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* Implementation of random_shuffle for linear case with cuda kernels and tests.
* Implemented random_shuffle with cuda kernels. Final revision.
* - finally gruCell_bp is completed
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* Dropout op cuda helper implementation.
* Implemented dropout_bp cuda helper.
* Implemented alpha_dropout_bp with cuda kernel helpers.
* Refactored helper.
* Implementation of suppresion helper with cuda kernels.
* - provide cpu code fot hsvToRgb, rgbToHsv, adjustHue
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* Using sort by value method.
* Implementation of image.non_max_suppression op cuda-based helper.
* - correcting and testing adjust_hue, adjust_saturation cpu/cuda code
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* Added cuda device prefixes to declarations.
* Implementation of hashcode op with cuda helper. Initital revision.
* rnn cu impl removed
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* initial commit
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* Added gradcheck test for dynamic_partition_bp op.
* - implementation of dilation op (cpu and cuda)
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* Fixed broadcast_dynamic_shape 1D case and tests.
* Fixed usage of default integer arguments.
* Fixed dynamic_partition_bp op and tests.
* Eliminated test with grad check for dynamic_partition_bp op.
* start working on cuda svd - porting available corresponding api from cuSOLVER library
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* provide prelu_bp
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* - provide gruCell_bp (old version ??)
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* - polishing cumsum_bp and cumprod_bp tests
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* provide sparseSoftmaxCrossEntropyWithLogits and sparseSoftmaxCrossEntropyWithLogits_grad
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* Fixed atomicMul with float input/output
* implementation of cuda kernel for triu_bp operation
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* Refactored lup helper to add parrallel computing.
* cusolver libraries
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* uncomment cuSolver APIs in svd.cu
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* cusolver var
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* - further work on cuSolver svd
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* Implement usage of cuda solver to LUP decomposition.
* - correct naames in lup functions
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* correct svdQR cuda
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* - provide transpositions of input matrices in case of c order in svdCudaQR
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* Fixed implementation issues with LUP usign cuda solver.
* Implementation of matrix_determinant helper with cuda kernels. Working revision.
* Implemented log_matrix_determinant helper with cuda kernels.
* - implementation of batched cuda svd
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* Refactored cholesky helper and implementation of cuda solver cholesky batch.
* - implementation of cuda kernel for tile bp
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* Implementation of cholesky and logdet with cuda kernels.
* - implementation of cuda kernel for sru_bidirectional
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* Fixed cholesky helper.
* Cholesky op helper implementation. Working double-based cublas implementation.
* bad import excluded
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* Finished with cuda implementation of cholesky helper and tests.
* - implementation of cuda kernel for sru_bidirectional_backprop operation
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* Implementation of matrix_inverse op helper with cuda kernels. The first revision.
* - start working on gruCell_bp
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* Implementation of matrix_inverse helper.
* - further work on new gruCell_bp
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* cuBLAS related fixes
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* calculateOutputShapes() now passes device buffers as well
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* special concat/average/accumulate init host pointers now
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* few more tweaks
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* additional CudaDataBufferFactory signatures certain for data types
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* cuSolver host buffer
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* buffer to buffer memcpy host ptr allocation
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