* one range test
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* few Context convenience singatures
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* one more range test
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* "range" "fix"
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* adjuct_contrast_v2 now allows scale factor to be provided via input_variable
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* adjust_contrast now allows scale factor as variable too
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* bitcast shape tests
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* BitCast import dtype added
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* few more BitCast signatures
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* - platform helpers can be disabled on per-op basis now via Context::allowHelpers
- java has access to it as well
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* global platform-helpers trigger
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* few signatures renamed
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* - few new env variables to follow
- maxThreads/masterThreads differentiation
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* Javadoc update
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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)
Signed-off-by: Yurii <yurii@skymind.io>
* 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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