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* Add block evaluationto CwiseUnaryOp and add PreferBlockAccess enum to all ↵Gravatar Eugene Zhulenev2018-08-10
| | | | evaluators
* Fix bug in a test + compilation errorsGravatar Eugene Zhulenev2018-08-09
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* Merged with upstream eigenGravatar Eugene Zhulenev2018-08-08
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| * Merged in codeplaysoftware/eigen-upstream-pure/constructor_error_clang (pull ↵Gravatar Benoit Steiner2018-08-02
| |\ | | | | | | | | | | | | | | | request PR-451) Fixing ambigous constructor error for Clang compiler.
| * | fixing compilation error for cxx11_tensor_trace.cpp error on Microsoft ↵Gravatar Mehdi Goli2018-08-02
| | | | | | | | | | | | Visual Studio.
| | * Fixing ambigous constructor error for Clang compiler.Gravatar Mehdi Goli2018-08-02
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| * Merged in paultucker/eigen (pull request PR-431)Gravatar Benoit Steiner2018-08-01
| |\ | | | | | | | | | | | | | | | Optional ThreadPoolDevice allocator Approved-by: Benoit Steiner <benoit.steiner.goog@gmail.com>
* | | Merged latest changes from upstream/eigenGravatar Eugene Zhulenev2018-08-01
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* | | Add block evaluation support to TensorOpsGravatar Eugene Zhulenev2018-07-31
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| * | Merged in ezhulenev/eigen/tiling_3 (pull request PR-438)Gravatar Gael Guennebaud2018-07-31
| |\ \ | |/ / |/| | | | | Tiled tensor executor
* | | Rename Index to StorageIndex + use Eigen::Array and Eigen::Map when possibleGravatar Eugene Zhulenev2018-07-27
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* | | Add tiled evaluation support to TensorExecutorGravatar Eugene Zhulenev2018-07-25
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* | | TensorBlockIOGravatar Eugene Zhulenev2018-07-23
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| | * Add test coverage for ThreadPoolDevice optional allocator.Gravatar Paul Tucker2018-07-19
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| * | Account for missing change on commit "Remove SimpleThreadPool and..."Gravatar Gustavo Lima Chaves2018-07-23
|/ / | | | | | | | | | | "... always use {NonBlocking}ThreadPool". It seems the non-blocking implementation was me the default/only one, but a reference to the old name was left unmodified. Fix that.
* | Initial support of TensorBlockGravatar Eugene Zhulenev2018-07-20
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* | Move cxx11_tensor_uint128 test under an EIGEN_TEST_CXX11 guardedGravatar Gustavo Lima Chaves2018-07-20
| | | | | | | | | | | | | | | | block Builds configured without the -DEIGEN_TEST_CXX11=ON flag would fail right away without this, as this test seems to rely on those language features. The skip under compilation with MSVC was kept.
* | bug #1569: fix Tensor<half>::mean() on AVX with respective unit test.Gravatar Gael Guennebaud2018-07-19
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* | Added a move constructor and move assignment operator to Tensor and wrote ↵Gravatar Viktor Csomor2018-02-07
| | | | | | | | some tests.
* | applying EIGEN_DECLARE_TEST to *gpu* testsGravatar Deven Desai2018-07-17
| | | | | | | | | | | | | | | | | | | | | | | | | | Also, a few minor fixes for GPU tests running in HIP mode. 1. Adding an include for hip/hip_runtime.h in the Macros.h file For HIP __host__ and __device__ are macros which are defined in hip headers. Their definitions need to be included before their use in the file. 2. Fixing the compile failure in TensorContractionGpu introduced by the commit to "Fuse computations into the Tensor contractions using output kernel" 3. Fixing a HIP/clang specific compile error by making the struct-member assignment explicit
* | Get rid of EIGEN_TEST_FUNC, unit tests must now be declared with ↵Gravatar Gael Guennebaud2018-07-17
| | | | | | | | | | | | | | | | | | EIGEN_DECLARE_TEST(mytest) { /* code */ }. This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
* | Fuse computations into the Tensor contractions using output kernelGravatar Eugene Zhulenev2018-07-10
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* Simplify handling and non-splitted tests and include split_test_helper.h ↵Gravatar Gael Guennebaud2018-07-16
| | | | instead of re-generating it. This also allows us to modify it without breaking existing build folder.
* Fix usage of EIGEN_SPLIT_LARGE_TESTS=ON: some unit tests, such as ↵Gravatar Gael Guennebaud2018-07-16
| | | | indexed_view have to be split unconditionally.
* Add unit test for -Tensor<complex> on GPUGravatar Gael Guennebaud2018-07-12
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* Fix cxx11_tensor_fft not building on Windows.Gravatar Thales Sabino2018-07-12
| | | | | | The type used in Eigen::DSizes needs to be at least 8 bytes long. Internally Tensor tries to convert this to an __int64 on Windows and this fails to build. On Linux, long and long long are both 8 byte integer types. * * * Changing from "long long" to "std::int64_t".
* merging updates from upstreamGravatar Deven Desai2018-07-11
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| * bug #1567: add optimized path for tensor broadcasting and 'Channel First' shapeGravatar Gael Guennebaud2018-07-09
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* | merging the CUDA and HIP implementation for the Tensor directory and the ↵Gravatar Deven Desai2018-06-20
| | | | | | | | unit tests
* | removing the *Hip files from the unsupported/Eigen/CXX11/src/Tensor and ↵Gravatar Deven Desai2018-06-20
| | | | | | | | unsupported/test directories
* | renaming *Cuda files to *Gpu in the unsupported/Eigen/CXX11/src/Tensor and ↵Gravatar Deven Desai2018-06-20
| | | | | | | | unsupported/test directories
* | updates based on PR feedbackGravatar Deven Desai2018-06-14
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | There are two major changes (and a few minor ones which are not listed here...see PR discussion for details) 1. Eigen::half implementations for HIP and CUDA have been merged. This means that - `CUDA/Half.h` and `HIP/hcc/Half.h` got merged to a new file `GPU/Half.h` - `CUDA/PacketMathHalf.h` and `HIP/hcc/PacketMathHalf.h` got merged to a new file `GPU/PacketMathHalf.h` - `CUDA/TypeCasting.h` and `HIP/hcc/TypeCasting.h` got merged to a new file `GPU/TypeCasting.h` After this change the `HIP/hcc` directory only contains one file `math_constants.h`. That will go away too once that file becomes a part of the HIP install. 2. new macros EIGEN_GPUCC, EIGEN_GPU_COMPILE_PHASE and EIGEN_HAS_GPU_FP16 have been added and the code has been updated to use them where appropriate. - `EIGEN_GPUCC` is the same as `(EIGEN_CUDACC || EIGEN_HIPCC)` - `EIGEN_GPU_DEVICE_COMPILE` is the same as `(EIGEN_CUDA_ARCH || EIGEN_HIP_DEVICE_COMPILE)` - `EIGEN_HAS_GPU_FP16` is the same as `(EIGEN_HAS_CUDA_FP16 or EIGEN_HAS_HIP_FP16)`
* | syncing this fork with upstreamGravatar Deven Desai2018-06-13
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| | * Activate dgmres unit testGravatar Gael Guennebaud2018-07-02
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| * Merge from eigen/eigenGravatar Michael Figurnov2018-06-07
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| | * Merge from eigen/eigen.Gravatar Michael Figurnov2018-06-07
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| | * | Fix compilation of special functions without C99 math.Gravatar Michael Figurnov2018-06-07
| | | | | | | | | | | | | | | | | | | | | | | | The commit with Bessel functions i0e and i1e placed the ifdef/endif incorrectly, causing i0e/i1e to be undefined when EIGEN_HAS_C99_MATH=0. These functions do not actually require C99 math, so now they are always available.
| | | * Fix typos found using codespellGravatar Gael Guennebaud2018-06-07
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| * | | Derivative of the incomplete Gamma function and the sample of a Gamma random ↵Gravatar Michael Figurnov2018-06-06
| |/ / | | | | | | | | | | | | | | | | | | | | | | | | | | | variable. In addition to igamma(a, x), this code implements: * igamma_der_a(a, x) = d igamma(a, x) / da -- derivative of igamma with respect to the parameter * gamma_sample_der_alpha(alpha, sample) -- reparameterization derivative of a Gamma(alpha, 1) random variable sample with respect to the alpha parameter The derivatives are computed by forward mode differentiation of the igamma(a, x) code. Although gamma_sample_der_alpha can be implemented via igamma_der_a, a separate function is more accurate and efficient due to analytical cancellation of some terms. All three functions are implemented by a method parameterized with "mode" that always computes the derivatives, but does not return them unless required by the mode. The compiler is expected to (and, based on benchmarks, does) skip the unnecessary computations depending on the mode.
* / / Adding support for using Eigen in HIP kernels.Gravatar Deven Desai2018-06-06
|/ / | | | | | | | | | | | | | | | | This commit enables the use of Eigen on HIP kernels / AMD GPUs. Support has been added along the same lines as what already exists for using Eigen in CUDA kernels / NVidia GPUs. Application code needs to explicitly define EIGEN_USE_HIP when using Eigen in HIP kernels. This is because some of the CUDA headers get picked up by default during Eigen compile (irrespective of whether or not the underlying compiler is CUDACC/NVCC, for e.g. Eigen/src/Core/arch/CUDA/Half.h). In order to maintain this behavior, the EIGEN_USE_HIP macro is used to switch to using the HIP version of those header files (see Eigen/Core and unsupported/Eigen/CXX11/Tensor) Use the "-DEIGEN_TEST_HIP" cmake option to enable the HIP specific unit tests.
| * Performance improvements to tensor broadcast operationGravatar Vamsi Sripathi2018-05-23
|/ | | | | | 1. Added new packet functions using SIMD for NByOne, OneByN cases 2. Modified existing packet functions to reduce index calculations when input stride is non-SIMD 3. Added 4 test cases to cover the new packet functions
* Exponentially scaled modified Bessel functions of order zero and one.Gravatar Michael Figurnov2018-05-31
| | | | | | The functions are conventionally called i0e and i1e. The exponentially scaled version is more numerically stable. The standard Bessel functions can be obtained as i0(x) = exp(|x|) i0e(x) The code is ported from Cephes and tested against SciPy.
* Use numext::maxi & numext::mini.Gravatar Rasmus Munk Larsen2018-05-14
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* Add vectorized clip functor for Eigen Tensors.Gravatar Rasmus Munk Larsen2018-05-14
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* Fix "used uninitialized" warningsGravatar Gael Guennebaud2018-04-24
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* Workaround warningGravatar Gael Guennebaud2018-04-24
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* Recent Adolc versions require C++11Gravatar Christoph Hertzberg2018-04-13
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* Update the padding computation for PADDING_SAME to be consistent with ↵Gravatar Benoit Steiner2018-01-30
|\ | | | | | | TensorFlow.
* | Disable use of recurrence for computing twiddle factors. Fixes FFT precision ↵Gravatar RJ Ryan2017-12-31
| | | | | | | | issues for large FFTs. https://github.com/tensorflow/tensorflow/issues/10749#issuecomment-354557689
| * Update the padding computation for PADDING_SAME to be consistent with ↵Gravatar Yangzihao Wang2017-12-12
|/ | | | TensorFlow.
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