| /external/eigen/doc/ |
| UsingBlasLapackBackends.dox | 29 * Content : Documentation on the use of BLAS/LAPACK libraries through Eigen
33 namespace Eigen {
35 /** \page TopicUsingBlasLapack Using BLAS/LAPACK from %Eigen
38 Since %Eigen version 3.3 and later, any F77 compatible BLAS or LAPACK libraries can be used as backends for dense matrix products and dense matrix decompositions.
39 For instance, one can use <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php">IntelŪ MKL</a>, Apple's Accelerate framework on OSX, <a href="http://www.openblas.net/">OpenBLAS</a>, <a href="http://www.netlib.org/lapack">Netlib LAPACK</a>, etc.
44 For LAPACK, you must also link to the standard <a href="http://www.netlib.org/lapack/lapacke.html">Lapacke</a> library, which is used as a convenient think layer between %Eigen's C++ code and LAPACK F77 interface. Then you must activate their usage by defining one or multiple of the following macros (\b before including any %Eigen's header):
59 When doing so, a number of %Eigen's algorithms are silently substituted with calls to BLAS or LAPACK routines.
63 The breadth of %Eigen functionality that can be substituted is listed in the table below.
109 <tr><td>Eigen-value decompositions \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\cod
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| UsingIntelMKL.dox | 29 * Content : Documentation on the use of Intel MKL through Eigen
33 namespace Eigen {
35 /** \page TopicUsingIntelMKL Using IntelŪ MKL from %Eigen
37 <!-- \section TopicUsingIntelMKL_Intro Eigen and IntelŪ Math Kernel Library (IntelŪ MKL) -->
39 Since %Eigen version 3.1 and later, users can benefit from built-in IntelŪ Math Kernel Library (MKL) optimizations with an installed copy of Intel MKL 10.3 (or later).
41 <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php"> Intel MKL </a> provides highly optimized multi-threaded mathematical routines for x86-compatible architectures.
47 Using Intel MKL through %Eigen is easy:
48 -# define the \c EIGEN_USE_MKL_ALL macro before including any %Eigen's header
52 When doing so, a number of %Eigen's algorithms are silently substituted with calls to Intel MKL routines.
101 - Intel MKL can be purchased and downloaded <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php">here</a>
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| /external/eigen/test/ |
| mpl2only.cpp | 1 // This file is part of Eigen, a lightweight C++ template library
11 #include <Eigen/Dense>
12 #include <Eigen/SparseCore>
13 #include <Eigen/SparseLU>
14 #include <Eigen/SparseQR>
15 #include <Eigen/Sparse>
16 #include <Eigen/IterativeLinearSolvers>
17 #include <Eigen/Eigen>
|
| bug1213.h | 2 #include <Eigen/Core>
5 bool bug1213_2(const Eigen::Matrix<T,dim,1>& x);
7 bool bug1213_1(const Eigen::Vector3f& x);
|
| bug1213_main.cpp | 13 bool bug1213_2(const Eigen::Matrix<T,dim,1>& )
18 template bool bug1213_2<float,3>(const Eigen::Vector3f&);
|
| /external/tensorflow/tensorflow/core/lib/bfloat16/ |
| bfloat16.cc | 18 #include "third_party/eigen3/Eigen/Core"
22 B16_DEVICE_FUNC bfloat16::operator Eigen::half() const {
23 return static_cast<Eigen::half>(float(*this));
|
| /external/tensorflow/tensorflow/core/framework/ |
| tensor_types.h | 19 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
24 template <typename T, int NDIMS = 1, typename IndexType = Eigen::DenseIndex>
27 typedef Eigen::TensorMap<Eigen::Tensor<T, NDIMS, Eigen::RowMajor, IndexType>,
28 Eigen::Aligned>
30 typedef Eigen::TensorMap<
31 Eigen::Tensor<const T, NDIMS, Eigen::RowMajor, IndexType>, Eigen::Aligned
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| /external/eigen/Eigen/src/Core/functors/ |
| TernaryFunctors.h | 1 // This file is part of Eigen, a lightweight C++ template library
13 namespace Eigen {
23 } // end namespace Eigen
|
| /external/eigen/unsupported/Eigen/src/SpecialFunctions/ |
| SpecialFunctionsHalf.h | 1 // This file is part of Eigen, a lightweight C++ template library
11 namespace Eigen {
15 template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half lgamma(const Eigen::half& a) {
16 return Eigen::half(Eigen::numext::lgamma(static_cast<float>(a)));
18 template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half digamma(const Eigen::half& a) {
19 return Eigen::half(Eigen::numext::digamma(static_cast<float>(a)))
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| SpecialFunctionsArrayAPI.h | 1 // This file is part of Eigen, a lightweight C++ template library
14 namespace Eigen {
24 * \sa Eigen::igammac(), Eigen::lgamma()
27 inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_igamma_op<typename Derived::Scalar>, const Derived, const ExponentDerived>
28 igamma(const Eigen::ArrayBase<Derived>& a, const Eigen::ArrayBase<ExponentDerived>& x)
30 return Eigen::CwiseBinaryOp<Eigen::internal::scalar_igamma_op<typename Derived::Scalar>, const Derived, const ExponentDerived>
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| /frameworks/native/libs/vr/libdvrcommon/include/private/dvr/ |
| types.h | 6 #include <private/dvr/eigen.h>
21 using vec2f = Eigen::Vector2f;
22 using vec2d = Eigen::Vector2d;
23 using vec2i = Eigen::Vector2i;
26 using vec3f = Eigen::Vector3f;
27 using vec3d = Eigen::Vector3d;
28 using vec3i = Eigen::Vector3i;
31 using vec4f = Eigen::Vector4f;
32 using vec4d = Eigen::Vector4d;
33 using vec4i = Eigen::Vector4i
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| /external/tensorflow/tensorflow/core/kernels/ |
| conv_ops_gpu_2.cu.cc | 27 typedef Eigen::GpuDevice GPUDevice;
30 Eigen::DenseIndex>;
31 template struct functor::InflatePadAndShuffle<GPUDevice, Eigen::half, 4, int>;
32 template struct functor::InflatePadAndShuffle<GPUDevice, Eigen::half, 4,
33 Eigen::DenseIndex>;
|
| split_lib.h | 20 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
30 const Eigen::DSizes<Eigen::DenseIndex, 2>& slice_indices,
31 const Eigen::DSizes<Eigen::DenseIndex, 2>& slice_sizes);
38 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
39 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes);
43 struct Split<Eigen::ThreadPoolDevice, T>
[all...] |
| cwise_op_gpu_inverse.cu.cc | 23 DEFINE_UNARY4(inverse, Eigen::half, float, double, int64);
24 DEFINE_SIMPLE_BINARY3(inverse_grad, Eigen::half, float, double);
|
| cwise_op_gpu_rsqrt.cu.cc | 23 DEFINE_UNARY3(rsqrt, Eigen::half, float, double);
24 DEFINE_SIMPLE_BINARY3(rsqrt_grad, Eigen::half, float, double);
|
| cwise_op_gpu_sigmoid.cu.cc | 23 DEFINE_UNARY3(sigmoid, Eigen::half, float, double);
24 DEFINE_SIMPLE_BINARY3(sigmoid_grad, Eigen::half, float, double);
|
| cwise_op_gpu_sqrt.cu.cc | 23 DEFINE_UNARY3(sqrt, Eigen::half, float, double);
24 DEFINE_SIMPLE_BINARY3(sqrt_grad, Eigen::half, float, double);
|
| cwise_op_gpu_tanh.cu.cc | 23 DEFINE_UNARY3(tanh, Eigen::half, float, double);
24 DEFINE_SIMPLE_BINARY3(tanh_grad, Eigen::half, float, double);
|
| /external/eigen/doc/examples/ |
| Cwise_erf.cpp | 1 #include <Eigen/Core>
2 #include <unsupported/Eigen/SpecialFunctions>
4 using namespace Eigen;
|
| Cwise_erfc.cpp | 1 #include <Eigen/Core>
2 #include <unsupported/Eigen/SpecialFunctions>
4 using namespace Eigen;
|
| Cwise_lgamma.cpp | 1 #include <Eigen/Core>
2 #include <unsupported/Eigen/SpecialFunctions>
4 using namespace Eigen;
|
| Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp | 2 #include <Eigen/Dense>
5 using namespace Eigen;
9 Eigen::MatrixXf m(2,4);
10 Eigen::VectorXf v(2);
|
| /external/eigen/unsupported/test/ |
| cxx11_tensor_dimension.cpp | 1 // This file is part of Eigen, a lightweight C++ template library
12 #include <Eigen/CXX11/Tensor>
14 using Eigen::Tensor;
19 Eigen::DSizes<int, 3> dimensions(2,3,7);
21 VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
22 VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3);
23 VERIFY_IS_EQUAL((int)Eigen::internal::array_get<2>(dimensions), 7);
32 Eigen::Sizes<2,3,7> dimensions;
34 VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
35 VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3)
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| /external/eigen/demos/opengl/ |
| camera.h | 1 // This file is part of Eigen, a lightweight C++ template library
13 #include <Eigen/Geometry>
22 inline Frame(const Eigen::Vector3f& pos = Eigen::Vector3f::Zero(),
23 const Eigen::Quaternionf& o = Eigen::Quaternionf())
32 Eigen::Quaternionf orientation;
33 Eigen::Vector3f position;
60 void setPosition(const Eigen::Vector3f& pos);
61 inline const Eigen::Vector3f& position(void) const { return mFrame.position;
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| /external/eigen/lapack/ |
| lapack_common.h | 1 // This file is part of Eigen, a lightweight C++ template library
14 #include "../Eigen/src/misc/lapack.h"
20 typedef Eigen::Map<Eigen::Transpositions<Eigen::Dynamic,Eigen::Dynamic,int> > PivotsType;
|
