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340 Commits

Author SHA1 Message Date
Gael Guennebaud
f8d653d1f9 bump to 3.3.6 2018-12-10 14:46:51 +01:00
Gael Guennebaud
b942bb0043 workaround "may be used uninitialized" warning
(grafted from bff90bf270
)
2018-12-08 18:58:28 +01:00
Gael Guennebaud
f1ffadb6e0 fix EIGEN_GEBP_2PX4_SPILLING_WORKAROUND for non vectorized type, and non x86/64 target
(grafted from 426bce7529
)
2018-12-08 09:44:21 +01:00
Gael Guennebaud
204d1f1456 Fix noise in sparse_basic_3 (numerical cancellation)
(grafted from cd25b538ab
)
2018-12-08 00:13:37 +01:00
Gael Guennebaud
c285ed1033 Fix noise in lu unit test 2018-12-08 00:05:38 +01:00
Christoph Hertzberg
818bf74b18 Add default constructor to Bar to make test compile again with clang-3.8
(grafted from ea60a172cf
)
2018-11-23 14:24:22 +01:00
Gael Guennebaud
9d56215db8 bug #1636: fix gemm performance issue with gcc>=6 and no FMA
(grafted from 4e7746fe22
)
2018-12-07 09:15:46 +01:00
Gael Guennebaud
c4ea9a916f bug #1637: workaround register spilling in gebp with clang>=6.0+AVX+FMA
(grafted from f233c6194d
)
2018-12-07 10:01:09 +01:00
Christoph Hertzberg
24d56f2e0e bug #1635: Use infinity from Numtraits instead of creating it manually.
(grafted from c1d356e8b4
)
2018-12-05 15:01:04 +01:00
Christoph Hertzberg
b9a2a8d2aa bug #785: Make Cholesky decomposition work for empty matrices
(grafted from 919414b9fe
)
2018-12-03 16:18:15 +01:00
Gael Guennebaud
5c97b48c29 bug #1634: remove double copy in move-ctor of non movable Matrix/Array
(grafted from ab4df3e6ff
)
2018-11-30 21:25:51 +01:00
Gael Guennebaud
a2d6c106a4 Workaround weird MSVC bug
(grafted from 4b2cebade8
)
2018-11-21 15:53:37 +01:00
Gael Guennebaud
40ddac243e Limit the size of the toc
(grafted from dffd1e11de
)
2018-11-09 13:52:34 +01:00
Gael Guennebaud
065c366b40 Update doxy hacks wrt doxygen 1.8.13/14
(grafted from a88e0a0e95
)
2018-11-09 13:52:10 +01:00
Gael Guennebaud
116dbf2c28 fix market IO 2018-11-09 13:56:17 +01:00
Matthieu Vigne
0ee9dede55 bug #1617: Fix SolveTriangular.solveInPlace crashing for empty matrix.
This made FullPivLU.kernel() crash when used on the zero matrix.
Add unit test for FullPivLU.kernel() on the zero matrix.
(grafted from 8d7a73e48e
)
2018-10-31 20:28:18 +01:00
Christoph Hertzberg
d107a371c6 Fix most Doxygen warnings. Also add links to stable documentation from unsupported modules (by using the corresponding Doxytags file). 2018-10-19 21:10:28 +02:00
Christoph Hertzberg
a4afa90d16 bug #1606: Explicitly set the standard before find_package(StandardMathLibrary). Also replace EIGEN_COMPILER_SUPPORT_CXX11 in favor of EIGEN_COMPILER_SUPPORT_CPP11. 2018-10-19 17:20:51 +02:00
Gael Guennebaud
e154c87504 fix a doxygen issue
(grafted from 774bb9d6f7
)
2018-10-08 09:30:15 +02:00
Christoph Hertzberg
fcc41f1b9a Fix a lot of Doxygen warnings in Tensor module
(grafted from 3f2c8b7ff0
)
2018-10-09 20:22:47 +02:00
Gael Guennebaud
9a53659b08 fix typo in doc
(grafted from 1dcf5a6ed8
)
2018-10-17 09:29:36 +02:00
Christoph Hertzberg
9ccbaaf3dd Explicitly convert 0 to Scalar for custom types
(grafted from 24dc076519
)
2018-10-12 10:22:19 +02:00
Gael Guennebaud
1d5581ead2 Workaround gcc bug making it trigger an invalid warning 2018-10-07 09:23:15 +02:00
Gael Guennebaud
3636a64667 bug #1605: workaround ABI issue with vector types (aka __m128) versus scalar types (aka float)
(grafted from de2efbc43c
)
2018-10-01 23:45:55 +02:00
Gael Guennebaud
148e579cc0 #pragma GCC diagnostic push/pop is not supported prioro to gcc 4.6 2018-09-27 09:23:54 +02:00
Christoph Hertzberg
64ec5a1a6b Change include order to make SparsePlugin work 2018-09-22 10:26:21 +02:00
Gael Guennebaud
2c932556fc Add missing plugins to DynamicSparseMatrix -- fix sparse_extra_3
(grafted from 4291f167ee
)
2018-09-21 14:53:43 +02:00
Gael Guennebaud
bc000deaae Fix conjugate-gradient for very small rhs
(grafted from 1141bcf794
)
2018-09-13 23:53:28 +02:00
Christoph Hertzberg
92cd158c01 Disable type-limits warnings for g++ < 4.8, and shadow warnings for all g++ versions 2018-09-12 14:51:19 +02:00
Christoph Hertzberg
80473b48bb EIGEN_UNUSED is not supported by g++4.7 (and not portable)
(grafted from ba2c8efdcf
)
2018-09-12 11:49:10 +02:00
Christoph Hertzberg
3b92f547f5 Fix more shadowing typedefs 2018-09-08 23:47:53 +02:00
Christoph Hertzberg
718e954df4 Fix shadowing typedefs 2018-09-07 16:34:04 +02:00
Christoph Hertzberg
1eef23a1eb Make param name and docs constistent for JacobiRotation::makeGivens
(manually grafted from c6066ac411
)
2018-09-06 18:22:50 +02:00
Alexey Frunze
af3656d4ca Fix build failures in matrix_power and matrix_exponential tests.
This fixes the static assertion complaining about double being
used in place of long double. This happened on MIPS32, where
double and long double have the same type representation.
This can be simulated on x86 as well if we pass -mlong-double-64
to g++.
(grafted from edeee16a16
)
2018-08-31 14:11:10 -07:00
Gael Guennebaud
7c6ed911b3 Fix legitimate "declaration shadows a typedef" warning 2018-07-09 11:03:39 +02:00
Christoph Hertzberg
5be00b0e29 Product of empty array must be 1 and not 0. 2018-08-30 17:14:52 +02:00
Christoph Hertzberg
03326d9155 Fix integer conversion warning 2018-08-30 17:12:53 +02:00
Christoph Hertzberg
6111dce0e8 gcc thinks this may not be initialized 2018-08-28 18:33:24 +02:00
Gael Guennebaud
f98992725c bug #1590: fix collision with some system headers defining the macro FP32 2018-08-28 13:20:45 +02:00
Gael Guennebaud
c5198249a9 Fix bad merge in previous commit 2018-08-28 12:58:19 +02:00
Alexey Frunze
e6c8d0b72d bug #1584: Improve random (avoid undefined behavior). 2018-08-08 20:19:32 -07:00
Christoph Hertzberg
caf7e6e7a7 Use Intel cast intrinsics, since MSVC does not allow direct casting.
Reported by David Winkler.
2018-08-24 19:04:33 +02:00
Christoph Hertzberg
ea7f12ebb5 Assertion depended on a not yet initialized value 2018-08-17 16:42:53 +02:00
Christoph Hertzberg
a9508054c3 Silence double-promotion warning 2018-08-17 16:39:43 +02:00
Christoph Hertzberg
7f3fff3fec Remove shadowing typedefs 2018-08-17 16:32:35 +02:00
Christoph Hertzberg
6ce4be6f84 Silence logical-op-parentheses warning 2018-08-17 16:30:32 +02:00
Christoph Hertzberg
ab95a8c1ef Silence unused parameter warning 2018-08-17 16:28:28 +02:00
Christoph Hertzberg
461620668c Silence double-promotion warning (when converting double to complex<long double>) 2018-08-17 16:26:11 +02:00
Gael Guennebaud
e4127b0f7d Fix fallback to BLAS for rankUptade 2018-08-16 18:14:27 +02:00
Gael Guennebaud
8180e13926 Fix half_float unit test wrt previous changeset 2018-07-31 09:58:24 +02:00
Gael Guennebaud
6eb4ce5f8e backport some nvcc 9 fixes 2018-07-30 14:45:08 +02:00
Christoph Hertzberg
b89d81b2a8 DIsable static assertions only when necessary and disable double-promotion warnings in that case as well 2018-07-26 00:07:07 +02:00
Christoph Hertzberg
73b1c0a660 fix warnings for doc-eigen-prerequisites 2018-07-24 21:59:15 +02:00
Christoph Hertzberg
4d05b107cf Allow to filter out build-error messages 2018-07-24 20:12:49 +02:00
Gael Guennebaud
7621bbc2a5 Add the cmake option "EIGEN_DASHBOARD_BUILD_TARGET" to control the build target in dashboard mode (e.g., ctest -D Experimental) 2018-07-16 17:59:30 +02:00
Gael Guennebaud
c15d736be3 Added tag 3.3.5 for changeset 81bdde705c 2018-07-23 11:33:47 +02:00
Gael Guennebaud
81bdde705c Bump to 3.3.5 2018-07-23 11:33:42 +02:00
Gael Guennebaud
06fc5761fa Oopps, EIGEN_COMP_MSVC is not available before including Eigen.
(grafted from de70671937
)
2018-07-20 17:51:17 +02:00
Gael Guennebaud
a185bc485c Disable optimization for sparse_product unit test with MSVC 2013, otherwise it takes several hours to build.
(grafted from 56a750b6cc
)
2018-07-20 08:36:38 -07:00
Gael Guennebaud
96134409fc Fix weird issue with MSVC 2013
(grafted from 3a2dc3869e
)
2018-07-18 02:26:43 -07:00
Gael Guennebaud
ab3fa2e123 Fix GeneralizedEigenSolver when requesting for eigenvalues only.
(grafted from a87cff20df
)
2018-07-14 09:38:49 +02:00
Gael Guennebaud
ae6e5caa40 Fix unit test
(grafted from a7b313a16c
)
2018-07-01 22:45:47 +02:00
Gael Guennebaud
483beabab9 bug #1560 fix product with a 1x1 diagonal matrix
(grafted from ee5864f72e
)
2018-06-25 10:30:12 +02:00
Jayaram Bobba
5c59564bfb fix AVX512 plog
(grafted from b7b868d1c4
)
2018-04-20 13:39:18 -07:00
Gael Guennebaud
1939c971a3 AVX512: _mm512_rsqrt28_ps is available for AVX512ER only
(grafted from 40b4bf3d32
)
2018-04-03 14:36:27 +02:00
Gael Guennebaud
c2f9e6cb37 AVX512: fix psqrt and prsqrt
(grafted from 7b0630315f
)
2018-04-03 14:12:50 +02:00
Rasmus Munk Larsen
1641a6cdd5 Fix typo in pbend for AltiVec.
(grafted from bda71ad394
)
2018-06-22 15:04:35 -07:00
Rasmus Munk Larsen
fea50d40ea Fix oversharding bug in parallelFor.
(grafted from 5418154a45
)
2018-06-20 17:51:48 -07:00
Gael Guennebaud
c1128efb6c fix md5sum of lapack_addons
(grafted from b8271bb368
)
2018-06-15 14:21:29 +02:00
Gael Guennebaud
20ca86888e bug #1555: compilation fix with XLC 2018-06-21 10:28:58 +02:00
Gael Guennebaud
36a1cd87d9 Fiw some warnings in dox examples
(grafted from c25034710e
)
2018-06-07 16:09:22 +02:00
Gael Guennebaud
523e442a7b Fix warning
(grafted from c723ffd763
)
2018-06-07 15:56:20 +02:00
Gael Guennebaud
48048172e5 Fix int versus Index
(grafted from 37348d03ae
)
2018-06-07 15:56:43 +02:00
Gael Guennebaud
e9bd839b13 Fix warning
(grafted from af7c83b9a2
)
2018-06-07 15:45:24 +02:00
Gael Guennebaud
3df78d5afc Fix MSVC warning C4290: C++ exception specification ignored except to indicate a function is not __declspec(nothrow)
(grafted from 7fe29aceeb
)
2018-06-07 15:36:20 +02:00
Gael Guennebaud
352489edbe Fix short vs long 2018-06-07 15:26:04 +02:00
Gael Guennebaud
450c5e5d27 Fix compilation with MSVC by reverting to char* for _mm_prefetch except for PGI (the later being the one that has the wrong prototype).
(grafted from 7134fa7a2e
)
2018-06-07 09:33:10 +02:00
Gael Guennebaud
64cc5f8512 Don't run hg on non mercurial clone
(grafted from 84868da904
)
2018-05-31 21:21:57 +02:00
Gael Guennebaud
656712d48f Doc: add aliasing in common pitfaffs.
(grafted from 6af1433cb5
)
2018-05-29 22:37:47 +02:00
Gael Guennebaud
971b32440c Define pcast<> for SSE types even when AVX is enabled. (otherwise float are silently reinterpreted as int instead of being converted)
(grafted from 647b724a36
)
2018-05-29 20:46:46 +02:00
Gael Guennebaud
bb87f618bf Fix compilation and SSE support with PGI compiler
(grafted from 49262dfee6
)
2018-05-29 15:09:31 +02:00
Jeff Trull
2f9de52245 Add tests for sparseQR results (value and size) covering bugs #1522 and #1544 2018-04-21 10:26:30 -07:00
Jeff Trull
2136cfa17e Make sparse QR result sizes consistent with dense QR, with the following rules:
1) Q is always square
2) Q*R*P' is valid and recovers the original matrix

This implies that the size of Q is the number of rows in the original matrix, square,
and that the size of R is the size of the original matrix.
2018-02-15 15:00:31 -08:00
Christoph Hertzberg
39125654ce bug #1544: Generate correct Q matrix in complex case. Original patch was by Jeff Trull in PR-386. 2018-05-17 19:17:01 +02:00
Gael Guennebaud
927d023cea Fix compilation with NEON+MSVC
(grafted from 6e7118265d
)
2018-04-26 10:50:41 +02:00
Gael Guennebaud
1e2d2693b9 bug #1428: atempt to make NEON vectorization compilable by MSVC.
The workaround is to wrap NEON packet types to make them different c++ types.
(grafted from e8ca5166a9
)
2018-04-24 11:19:49 +02:00
Gael Guennebaud
7634a44bfe Fix "used uninitialized" warnings
(grafted from 2f3287da7d
)
2018-04-24 17:17:25 +02:00
Gael Guennebaud
2480d04ac7 Workaround warning
(grafted from 3ffd449ef5
)
2018-04-24 17:11:51 +02:00
Gael Guennebaud
c92536d926 workaround MSVC 2013 compilation issue (ambiguous call)
(grafted from a57e6e5f0f
)
2018-04-23 15:31:51 +02:00
Gael Guennebaud
80af7d6a47 bug #1543: fix linear indexing in generic block evaluation (this completes the fix in commit 12efc7d41b
)
(grafted from 5679e439e0
)
2018-04-23 14:40:16 +02:00
Gael Guennebaud
87f9e301f9 Fix unit test
(grafted from 35b31353ab
)
2018-04-22 22:49:08 +02:00
Christoph Hertzberg
542fb03968 Fix enum-compare warning 2018-04-20 23:11:37 +02:00
Christoph Hertzberg
f90d136c84 Add parenthesis to fix compiler warnings 2018-04-15 18:43:56 +02:00
Gael Guennebaud
877a2b64c9 fix const cast in NEON
(grafted from 686fb57233
)
2018-04-18 18:46:34 +02:00
Dmitriy Korchemkin
e6577f3c30 Cast zeros to Scalar in RealSchur 2018-04-18 13:52:46 +03:00
Gael Guennebaud
69e01a2999 update cdash 2018-04-17 17:22:56 +02:00
Christoph Hertzberg
5f71579a2d Another fix to make boost::multiprecision compile again 2018-04-13 20:22:57 +02:00
Christoph Hertzberg
686e0749a5 Recent Adolc versions require C++11 2018-04-13 19:10:23 +02:00
Christoph Hertzberg
385d8b5e42 Make hypot_impl compile again for types with expression-templates (e.g., boost::multiprecision) 2018-04-13 19:01:37 +02:00
Christoph Hertzberg
4662c610c1 SelfAdjointView<...,Mode> causes a static assert since commit d820ab9edc 2018-04-13 19:00:34 +02:00
Gael Guennebaud
906a98fe39 fix linking issue
(grafted from 7a9089c33c
)
2018-04-13 08:51:47 +02:00
Gael Guennebaud
1c4fdad7bd bug #1520: workaround some -Wfloat-equal warnings by calling std::equal_to 2018-04-11 15:24:13 +02:00
Gael Guennebaud
3f711f3356 extend doxygen splitter for huge screens
(grafted from 79266fec75
)
2018-04-11 11:31:17 +02:00
Gael Guennebaud
b02ab76847 Update header/footer for doxygen 1.8.13
(grafted from 426052ef6e
)
2018-04-11 11:30:34 +02:00
Gael Guennebaud
5fec52ced1 Fix javascript hacks for oxygen 1.8.13
(grafted from 9c8decffbf
)
2018-04-11 11:30:14 +02:00
Gael Guennebaud
bde2bfcee8 bug #1538: update manual pages regarding BDCSVD.
(grafted from e798466871
)
2018-04-11 10:46:11 +02:00
Gael Guennebaud
eab7afe252 Fix MKL backend for symmetric eigenvalues on row-major matrices.
(grafted from add15924ac
)
2018-04-09 13:29:26 +02:00
Gael Guennebaud
81e94eea02 Fix cmake scripts with no fortran compiler
(grafted from c2624c0318
)
2018-04-07 08:45:19 +02:00
Gael Guennebaud
a2a2c3c865 bug #1509: fix computeInverseWithCheck for complexes
(grafted from 2f833b1c64
)
2018-04-04 15:47:46 +02:00
Gael Guennebaud
90cd199d4b Factories code between numext::hypot and scalar_hyot_op functor.
(grafted from 4213b63f5c
)
2018-04-04 15:12:43 +02:00
Gael Guennebaud
b18e2d422b bug #1521: avoid signalling NaN in hypot and make it std::complex<> friendly.
(grafted from e116f6847e
)
2018-04-04 13:47:23 +02:00
Gael Guennebaud
892c0a79ce bug #1494: makes pmin/pmax behave on Altivec/VSX as on x86 regading NaNs
(grafted from e91e314347
)
2018-04-04 11:39:19 +02:00
Gael Guennebaud
59398aa2bb comment unreachable code
(grafted from 112c899304
)
2018-04-03 23:16:43 +02:00
Gael Guennebaud
170914dbbc Fix compilation of product with inverse transpositions (e.g., mat * Transpositions().inverse())
(grafted from a1292395d6
)
2018-04-03 23:06:44 +02:00
Gael Guennebaud
866d222d60 commit 45e9c9996da790b55ed9c4b0dfeae49492ac5c46 (HEAD -> memory_fix)
Author: George Burgess IV <gbiv@google.com>
Date:   Thu Mar 1 11:20:24 2018 -0800

    Prefer `::operator new` to `new`

    The C++ standard allows compilers much flexibility with `new`
    expressions, including eliding them entirely
    (https://godbolt.org/g/yS6i91). However, calls to `operator new` are
    required to be treated like opaque function calls.

    Since we're calling `new` for side-effects other than allocating heap
    memory, we should prefer the less flexible version.

    Signed-off-by: George Burgess IV <gbiv@google.com>
(grafted from 8c7b5158a1
)
2018-04-03 17:15:38 +02:00
Gael Guennebaud
86a939451c bug #1527: fix support for MKL's VML (destination was not properly resized)
(grafted from dd4cc6bd9e
)
2018-04-03 17:11:15 +02:00
Gael Guennebaud
9ff3150243 bug #1528: better use numeric_limits::min() instead of 1/highest() that with underflow.
(grafted from c5b56f1fb2
)
2018-04-03 16:49:35 +02:00
Benoit Steiner
a7144f8d6a Made the TensorStorage class compile with clang 3.9
(grafted from de7b0fdea9
)
2017-02-28 13:52:22 -08:00
Gael Guennebaud
273738ba6f bug #1516: add assertion for out-of-range diagonal index in MatrixBase::diagonal(i)
(grafted from 8d0ffe3655
)
2018-04-03 16:15:43 +02:00
Gael Guennebaud
3fb42ff7b2 bug #1532: disable stl::*_negate in C++17 (they are deprecated)
(grafted from 407e3e2621
)
2018-04-03 15:59:30 +02:00
Gael Guennebaud
e90a14609a Fix uninitialized output argument.
(grafted from 524119d32a
)
2018-04-03 10:56:10 +02:00
Gael Guennebaud
ece56baba0 Merged in bfierz/eigen/3.3 (pull request PR-345)
Adds missing EIGEN_STRONG_INLINE to support MSVC properly inlining small vector calculations
2018-03-27 07:40:13 +00:00
Gael Guennebaud
1724dae8b8 Add static assertion for fixed sizes Ref<>
(grafted from f7d17689a5
)
2018-03-09 10:11:13 +01:00
Gael Guennebaud
190b46dd1f Implement better static assertion checking to make sure that the first assertion is a static one and not a runtime one.
(grafted from f6be7289d7
)
2018-03-09 10:00:51 +01:00
Gael Guennebaud
74daf12e52 Add static assertion on selfadjoint-view's UpLo parameter.
(grafted from d820ab9edc
)
2018-03-09 09:33:43 +01:00
Gael Guennebaud
c24844195d bug #1517: fix triangular product with unit diagonal and nested scaling factor: (s*A).triangularView<UpperUnit>()*B
(grafted from 5deeb19e7b
)
2018-02-09 16:52:35 +01:00
Gael Guennebaud
15752027ec Fix linear indexing in generic block evaluation.
(grafted from 12efc7d41b
)
2018-02-09 16:45:49 +01:00
Eugene Chereshnev
bfc66e8b9a Fix incorrect ldvt in LAPACKE call from JacobiSVD
(grafted from f558ad2955
)
2018-01-03 12:55:52 -08:00
Gael Guennebaud
b60cbbef37 fix compilation with old compiler 2017-12-15 17:53:48 +01:00
Gael Guennebaud
33b972d8b3 Fix compilation of stableNorm with some expressions as input
(grafted from 06bf1047f9
)
2017-12-15 15:15:37 +01:00
Gael Guennebaud
bb28a2aada fix warning 2017-12-15 14:43:33 +01:00
Gael Guennebaud
acd0ce11aa Fix cmake warning
(grafted from 31e0bda2e3
)
2017-12-14 15:48:27 +01:00
Basil Fierz
01fb621733 Adds missing EIGEN_STRONG_INLINE to support MSVC properly inlining small vector calculations
When working with MSVC often small vector operations are not properly inlined. This behaviour is observed even on the most recent compiler versions.
2017-10-26 22:44:28 +02:00
Benoit Steiner
71d1198ccd Merged in henryiii/eigen/henryiii/device33 (pull request PR-344)
Branch 3.3: Fixing missing inlines on device functions for newer CUDA cards
2017-10-21 01:59:01 +00:00
Henry Schreiner
95ec3232c6 Restore __device__ 2017-10-21 00:48:05 +00:00
Henry Schreiner
243249718b Adding missing inlines for CUDA and ARCH 6 2017-10-20 13:00:23 +00:00
Gael Guennebaud
32a6db0f8c bug #1468 (1/2) : add missing std:: to memcpy
(grafted from 8579195169
)
2017-09-22 09:23:24 +02:00
Gael Guennebaud
6fc0f2be70 Update documentation for aligned_allocator
(grafted from 7ad07fc6f2
)
2017-09-20 10:22:00 +02:00
Gael Guennebaud
70ac6c9230 Add C++11 max_digits10 for half.
(grafted from 9c353dd145
)
2017-09-06 10:22:47 +02:00
Gael Guennebaud
609e425166 Implement true compile-time "if" for apply_rotation_in_the_plane. This fixes a compilation issue for vectorized real type with missing vectorization for complexes, e.g. AVX512.
(grafted from b35d1ce4a5
)
2017-09-06 10:02:49 +02:00
Gael Guennebaud
4ead16cdd6 Fix mixing types in sparse matrix products.
(grafted from 80142362ac
)
2017-09-02 22:50:20 +02:00
Gael Guennebaud
361102f88b Merged in dtrebbien/eigen/patch-1 (pull request PR-312)
Work around a compilation error seen with nvcc V8.0.61
(grafted from fc39d5954b
)
2017-08-22 12:17:37 +00:00
Gael Guennebaud
5d40715db6 Handle min/max/inf/etc issue in cuda_fp16.h directly in test/main.h
(grafted from 304ef29571
)
2017-08-24 11:26:41 +02:00
Gael Guennebaud
e7c065ec71 bug #1462: remove all occurences of the deprecated __CUDACC_VER__ macro by introducing EIGEN_CUDACC_VER 2017-08-24 11:06:47 +02:00
Gael Guennebaud
18868228ad bug #336: improve doc for PlainObjectBase::Map
(grafted from 39864ebe1e
)
2017-08-22 17:18:43 +02:00
Gael Guennebaud
fbb0c510c5 Add missing scalar conversion
(grafted from 600e52fc7f
)
2017-08-22 17:06:57 +02:00
Gael Guennebaud
a8d2459f8e bug #1449: fix redux_3 unit test
(grafted from bc4dae9aeb
)
2017-08-22 15:59:08 +02:00
Gael Guennebaud
9a266e5118 bug #1461: fix compilation of Map<const Quaternion>::x()
(grafted from bc91a2df8b
)
2017-08-22 15:10:42 +02:00
Gael Guennebaud
51e1aa1539 Doc: warn about constness in LLT::solveInPlace
(grafted from b223918ea9
)
2017-08-22 14:12:47 +02:00
Jim Radford
0137ed4f19 LLT: const the arg to solveInPlace() to allow passing .transpose(), .block(), etc.
(grafted from 0c226644d8
)
2017-01-04 14:42:57 -08:00
Jim Radford
9d03711df8 LLT: avoid making a copy when decomposing in place
(grafted from be281e5289
)
2017-01-04 14:43:56 -08:00
Gael Guennebaud
1ca9072b51 Gub 1453: fix Map with non-default inner-stride but no outer-stride.
(grafted from e27f17bf5c
)
2017-08-22 13:27:37 +02:00
Gael Guennebaud
9fd138e2b3 Re-enable hidden doc in LLT
(grafted from 2c3d70d915
)
2017-08-22 12:04:09 +02:00
Gael Guennebaud
55fbf4fedd bug #1456: add perf recommendation for LLT and storage format
(grafted from 21d0a0bcf5
)
2017-08-22 12:46:35 +02:00
Gael Guennebaud
b87875abf8 bug #1455: Cholesky module depends on Jacobi for rank-updates.
(grafted from a6e7a41a55
)
2017-08-22 11:37:32 +02:00
Gael Guennebaud
ac2c97edff bug #1458: fix documentation of LLT and LDLT info() method.
(grafted from e6021cc8cc
)
2017-08-22 11:32:55 +02:00
Gael Guennebaud
292dea7922 Clarify MKL_DIRECT_CALL doc.
(grafted from 2810ba194b
)
2017-08-17 22:12:26 +02:00
Gael Guennebaud
070b5958e0 use MKL's lapacke.h header when using MKL
(grafted from f727844658
)
2017-08-17 21:58:39 +02:00
Gael Guennebaud
3108fbf767 Clarify doc regarding the usage of MKL_DIRECT_CALL
(grafted from 8c858bd891
)
2017-08-17 12:17:45 +02:00
Gael Guennebaud
9df7f3d8e9 Fix support for MKL's BLAS when using MKL_DIRECT_CALL.
(grafted from b95f92843c
)
2017-08-17 12:07:10 +02:00
Gael Guennebaud
782fd81dee Disable BDCSVD preallocation check.
(grafted from d580a90c9a
)
2017-07-20 10:03:54 +02:00
Gael Guennebaud
fa77d71335 Fix lazyness of operator* with CUDA 2017-07-20 09:47:28 +02:00
Gael Guennebaud
3d1795da28 Fix gcc7 warning: Wint-in-bool-context 2017-06-27 14:32:36 +02:00
Gael Guennebaud
d1c2d6683c Fix a gcc7 warning: Wint-in-bool-context
(grafted from b651ce0ffa
)
2017-06-26 09:58:28 +02:00
Christoph Hertzberg
d8cf158e06 Make sure CMAKE_Fortran_COMPILER is set before checking for Fortran functions 2017-06-20 16:31:53 +02:00
Gael Guennebaud
bc837b7975 bug #1436: fix compilation of Jacobi rotations with ARM NEON, some specializations of internal::conj_helper were missing.
(grafted from b240080e64
)
2017-06-15 10:16:30 +02:00
Gael Guennebaud
68e8f2b833 Added tag 3.3.4 for changeset 3dc3a0ea2d 2017-06-15 09:10:26 +02:00
Gael Guennebaud
3dc3a0ea2d bump to 3.3.4 2017-06-15 09:10:20 +02:00
Gael Guennebaud
79120a4c63 Enable Array(EigenBase<>) ctor for compatible scalar types only. This prevents nested arrays to look as being convertible from/to simple arrays.
(grafted from 9fbdf02059
)
2017-06-12 22:30:32 +02:00
Gael Guennebaud
e0412f18fd Fix compilation of streaming nested Array, i.e., cout << Array<Array<>>
(grafted from e43d8fe9d7
)
2017-06-12 22:26:26 +02:00
Gael Guennebaud
40b0c43bda Fix 1x1 case in Solve expression with EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION==RowMajor
(grafted from d9d7bd6d62
)
2017-06-12 22:25:02 +02:00
Gael Guennebaud
72f3e20e74 Fix LeastSquareDiagonalPreconditioner for complexes (issue introduced in previous commit)
(grafted from a7be4cd1b1
)
2017-06-09 11:57:53 +02:00
Gael Guennebaud
676a7a3271 fix compilation in C++98
(grafted from 8640093af1
)
2017-06-09 12:45:01 +02:00
Gael Guennebaud
f843239452 bug #1414: doxygen, add EigenBase to CoreModule
(grafted from 90168c003d
)
2017-06-09 14:01:44 +02:00
Gael Guennebaud
a4ab0c6b6a Fix compilation with some compilers
(grafted from a4fd4233ad
)
2017-06-09 23:02:02 +02:00
Gael Guennebaud
ef955ea8e5 fix tipo
(grafted from 50e09cca0f
)
2017-06-11 15:30:36 +02:00
NeroBurner
8bd392ca0e add cmake-option to enable/disable creation of tests
* * *
disable unsupportet/test when test are disabled
* * *
rename EIGEN_ENABLE_TESTS to BUILD_TESTING
* * *
consider BUILD_TESTING in blas
(grafted from c4fc2611ba
)
2017-01-02 09:09:21 +01:00
Gael Guennebaud
8d2ac85797 fix unit test
(grafted from 26a2c6fc16
)
2017-12-14 15:11:04 +01:00
Gael Guennebaud
6d6e5fcd43 Add possibility to overwrite EIGEN_STRONG_INLINE. 2017-12-14 14:47:38 +01:00
Gael Guennebaud
9c9e90f6db Fix packet and alignment propagation logic of Block<Xpr> expressions. In particular, (A+B).col(j) lost vectorisation.
(grafted from 9c3aed9d48
)
2017-12-14 14:24:33 +01:00
Gael Guennebaud
7ffa27f347 ignore all *build* sub directories
(grafted from 76c7dae600
)
2017-12-14 14:22:14 +01:00
Gael Guennebaud
c20043c8fd bug #1479: fix failure detection in LDLT
(grafted from 672bdc126b
)
2017-11-16 17:55:24 +01:00
Gael Guennebaud
d18877f18d bug #1485: fix linking issue of non template functions
(grafted from 7cc503f9f5
)
2017-11-15 21:33:37 +01:00
Justin Carpentier
02c0cef97f Use col method for column-major matrix
(grafted from a020d9b134
)
2017-10-17 21:51:27 +02:00
Gael Guennebaud
c8e663fe87 bug #1484: restore deleted line for 128 bits long doubles, and improve dispatching logic.
(grafted from 0a1cc73942
)
2017-11-10 10:25:41 +01:00
Gael Guennebaud
7a875acfb0 Fix overflow issues in BDCSVD
(grafted from e8468ea91b
)
2017-11-08 10:24:28 +01:00
Gael Guennebaud
3ec11d8f17 Fix compilation
(grafted from 7713e20fd2
)
2016-12-27 22:04:58 +01:00
Gael Guennebaud
ec067ac5e3 bug #1403: more scalar conversions fixes in BDCSVD
(grafted from 731c8c704d
)
2017-06-09 15:45:49 +02:00
Gael Guennebaud
316969d839 bug #1403: fix implicit scalar type conversion.
(grafted from 1bbcf19029
)
2017-06-09 14:44:02 +02:00
Gael Guennebaud
7a0a9581b5 bug #1405: enable StrictlyLower/StrictlyUpper triangularView as the destination of matrix*matrix products.
(grafted from ba5cab576a
)
2017-06-09 14:38:04 +02:00
Gael Guennebaud
8880be60fa fix compilation of Half in C++98 (issue introduced in previous commit)
(grafted from 26f552c18d
)
2017-06-09 13:36:58 +02:00
Gael Guennebaud
e41713d52e Fix compilation with gcc 4.3 and ARM NEON
(grafted from 1d59ca2458
)
2017-06-09 13:20:52 +02:00
Gael Guennebaud
b69e465d7a bug #1410: fix lvalue propagation of Array/Matrix-Wrapper with a const nested expression.
(grafted from fb1ee04087
)
2017-06-09 13:13:03 +02:00
Joao Rui Leal
0db83fc571 it is now possible to change Umfpack control settings before factorizations; added access to the report functions of Umfpack
(grafted from 95b804c0fe
)
2016-12-19 10:45:59 +00:00
Gael Guennebaud
1ac703f641 bug #1424: add numext::abs specialization for unsigned integer types. 2017-06-09 11:53:49 +02:00
Gael Guennebaud
2c32368642 Add missing std::numeric_limits specialization for half, and complete NumTraits<half>
(grafted from d588822779
)
2017-06-09 11:51:53 +02:00
Gael Guennebaud
db40309e70 bug #1423: fix LSCG\'s Jacobi preconditioner for row-major matrices.
(grafted from 682b2ef17e
)
2017-06-08 15:06:27 +02:00
Gael Guennebaud
e36c1f7501 bug #1435: fix aliasing issue in exressions like: A = C - B*A;
(grafted from 4bbc320468
)
2017-06-08 12:55:25 +02:00
Mmanu Chaturvedi
3aef5c1a2f Specializing numeric_limits For AutoDiffScalar
(grafted from 2971503fed
)
2017-05-23 17:12:36 -04:00
Gael Guennebaud
ab6bb89980 Fix compilation of matrix log with Map as input
(grafted from 26e8f9171e
)
2017-06-07 10:51:23 +02:00
Gael Guennebaud
983ace99d4 bug #1411: fix usage of alignment information in vectorization of quaternion product and conjugate.
(grafted from f2a553fb7b
)
2017-06-07 10:10:30 +02:00
Gael Guennebaud
72fa6775e8 bug #1417: make LinSpace compatible with std::complex
(grafted from 8508db52ab
)
2017-06-06 17:25:56 +02:00
Gael Guennebaud
9f25cdf4f6 Fix dense * sparse-selfadjoint-view product.
(grafted from 891ac03483
)
2017-04-25 13:58:10 +02:00
Gael Guennebaud
6e5edd68d3 Improve mixing of complex and real in the vectorized path of apply_rotation_in_the_plane
(grafted from d9084ac8e1
)
2017-04-14 11:05:13 +02:00
Gael Guennebaud
e8978ffa99 Fix unwanted Real to Scalar to Real conversions in column-pivoting QR.
(grafted from f75dfdda7e
)
2017-04-14 10:34:30 +02:00
Gael Guennebaud
c753fe7cc3 Improve cmake scripts for Pastix and BLAS detection.
(grafted from 0f83aeb6b2
)
2017-04-14 10:22:12 +02:00
Gael Guennebaud
e59e345720 better check array index before using it
(grafted from 89fd0c3881
)
2017-03-15 15:18:03 +01:00
Benoit Jacob
07c2244440 ARM prefetch fixes: Implement prefetch on ARM64. Do not clobber cc on ARM32. 2017-03-15 06:53:35 -04:00
Gael Guennebaud
1865dccd58 bug #1401: fix compilation of "cond ? x : -x" with x an AutoDiffScalar
(grafted from 970ff78294
)
2017-03-08 16:16:53 +01:00
Gael Guennebaud
f2e6ee9687 remove UTF8 symbol
(grafted from 5694315fbb
)
2017-03-07 10:53:47 +01:00
Gael Guennebaud
9219307e13 remove UTF8 symbols
(grafted from e958c2baac
)
2017-03-07 10:47:40 +01:00
Gael Guennebaud
f2e8f96151 bug #1400: fix stableNorm with EIGEN_DONT_ALIGN_STATICALLY
(grafted from 659087b622
)
2017-03-07 10:02:34 +01:00
Gael Guennebaud
faf8af25ed bug #1396: add some missing EIGEN_DEVICE_FUNC
(grafted from 4e98a7b2f0
)
2017-02-28 09:47:38 +01:00
Gael Guennebaud
106ba41c2a Fix typo.
(grafted from 478a9f53be
)
2017-02-28 09:32:45 +01:00
Benoit Steiner
87939ea0dd Added missing EIGEN_DEVICE_FUNC to the SelfCwise binary ops
(grafted from 889c606f8f
)
2017-02-27 17:17:47 -08:00
Benoit Steiner
e813640aa1 Added missing EIGEN_DEVICE_FUNC qualifiers to several nullary op methods.
(grafted from 193939d6aa
)
2017-02-27 17:11:47 -08:00
Benoit Steiner
612b8f2749 Declared the plset, ploadt_ro, and ploaddup packet primitives as usable within a gpu kernel
(grafted from ed4dc9d01a
)
2017-02-27 16:57:01 -08:00
Benoit Steiner
ead8e1b796 Added missing EIGEN_DEVICE_FUNC qualifiers.
(grafted from b1fc7c9a09
)
2017-02-27 16:48:30 -08:00
Benoit Steiner
3d4265f2d5 Added EIGEN_DEVICE_FUNC to make the prototype of the EigenBase override match that of DenseBase
(grafted from 554116bec1
)
2017-02-27 16:45:31 -08:00
Benoit Steiner
d66586ac90 Avoid unecessary float to double conversions.
(grafted from 34d9fce93b
)
2017-02-27 16:33:33 -08:00
Gael Guennebaud
44920624fb Added tag 3.3.3 for changeset 208058b9ad 2017-02-21 14:36:39 +01:00
Gael Guennebaud
208058b9ad bump to 3.3.3 2017-02-21 14:36:34 +01:00
Gael Guennebaud
b4218b8473 Use int32_t instead of int in NEON code. Some platforms with 16 bytes int supports ARM NEON.
(grafted from cbbf88c4d7
)
2017-02-17 14:39:02 +01:00
Gael Guennebaud
3c2f0812f6 bug #1394: fix compilation of SelfAdjointEigenSolver<Matrix>(sparse*sparse);
(grafted from 76687f385c
)
2017-02-20 14:27:26 +01:00
Gael Guennebaud
17bbd82f7d bug #1380: for Map<> as input of matrix exponential
(grafted from d8b1f6cebd
)
2017-02-20 14:06:06 +01:00
Gael Guennebaud
e1385337ff bug #1395: fix the use of compile-time vectors as inputs of JacobiSVD.
(grafted from 6572825703
)
2017-02-20 13:44:37 +01:00
Gael Guennebaud
d367ecb475 Silent warning.
(grafted from a811a04696
)
2017-02-20 10:14:21 +01:00
Gael Guennebaud
c3b658b2c9 Fix tracking of temporaries in unit tests
(grafted from deefa54a54
)
2017-02-19 10:32:54 +01:00
Gael Guennebaud
f9d655a8c8 Fix compilation.
(grafted from f8a55cc062
)
2017-02-18 10:08:13 +01:00
Gael Guennebaud
ad3e4d1a49 bug #1393: enable Matrix/Array explicit ctor from types with conversion operators (was ok with 3.2)
(grafted from 582b5e39bf
)
2017-02-17 14:10:57 +01:00
Gael Guennebaud
222ed66f79 Fix usage of CUDACC_VER 2017-02-20 08:16:54 +01:00
Gael Guennebaud
6bceebfabf bug #1391: include IO.h before DenseBase to enable its usage in DenseBase plugins. 2017-02-13 09:46:20 +01:00
Gael Guennebaud
2ca3eb8407 bug #1392: fix #include <Eigen/Sparse> with mpl2-only
(grafted from c16ee72b20
)
2017-02-11 10:35:01 +01:00
Gael Guennebaud
698205cddf Suppress warning 2017-02-10 21:30:31 +01:00
Gael Guennebaud
2ecb33820f Fix prunning in (sparse*sparse).pruned() when the result is nearly dense.
(grafted from a1ff24f96a
)
2017-02-10 13:59:32 +01:00
Gael Guennebaud
a0de6eb4ce Include clang in the list of non strict MSVC (just to be sure) 2017-02-10 13:41:52 +01:00
Alexander Neumann
7962ac1a58 fixed inlining issue with clang-cl on visual studio 2017-02-08 23:50:38 +01:00
Alexander Neumann
9c97b053f3 fixed compiling issue using clang-cl with visual studio 2017-02-08 23:50:09 +01:00
Gael Guennebaud
f61b0d56f0 Improve multi-threading heuristic for matrix products with a small number of columns.
(grafted from fc8fd5fd24
)
2017-02-07 17:19:59 +01:00
Gael Guennebaud
5087e016eb bug #1389: MSVC's std containers do not properly align in 64 bits mode if the requested alignment is larger than 16 bytes (e.g., with AVX)
(grafted from 4254b3eda3
)
2017-02-03 15:22:35 +01:00
Gael Guennebaud
fa9f5d7170 Fix compilation of JacobiSVD for vectors type
(grafted from 645a8e32a5
)
2017-01-31 16:22:54 +01:00
Gael Guennebaud
6975534cb2 bug #478: fix regression in the eigen decomposition of zero matrices.
(grafted from 53026d29d4
)
2017-01-31 14:22:42 +01:00
Gael Guennebaud
95c6d8db75 bug #1380: fix matrix exponential with Map<>
(grafted from 63de19c000
)
2017-01-30 13:55:27 +01:00
Gael Guennebaud
e0548e9ff3 bug #1384: fix evaluation of "sparse/scalar" that used the wrong evaluation path.
(grafted from c86911ac73
)
2017-01-30 13:38:24 +01:00
Gael Guennebaud
c289ef20f3 bug #1383: fix regression in LinSpaced for integers and high<low
(grafted from 850ca961d2
)
2017-01-25 18:13:53 +01:00
Gael Guennebaud
b8cf157e8c bug #1381: fix sparse.diagonal() used as a rvalue.
The problem was that is "sparse" is not const, then sparse.diagonal() must have the
LValueBit flag meaning that sparse.diagonal().coeff(i) must returns a const reference,
const Scalar&. However, sparse::coeff() cannot returns a reference for a non-existing
zero coefficient. The trick is to return a reference to a local member of
evaluator<SparseMatrix>.
(grafted from 296d24be4d
)
2017-01-25 17:39:01 +01:00
Gael Guennebaud
b4d2b404b0 bug #1383: Fix regression from 3.2 with LinSpaced(n,0,n-1) with n==0.
(grafted from d06a48959a
)
2017-01-25 15:27:13 +01:00
Gael Guennebaud
70fcaf9bd8 bug #1365: fix another type mismatch warning
(sync is set from and compared to an Index)
2016-12-28 23:35:43 +01:00
Gael Guennebaud
2f31c6b1d8 bug #1369: fix type mismatch warning.
Returned values of omp thread id and numbers are int,
o let's use int instead of Index here.
(grafted from 97812ff0d3
)
2016-12-28 23:29:35 +01:00
Gael Guennebaud
9e55467b4c bug #1375: fix cmake installation with cmake 2.8
(grafted from 156e6234f1
)
2017-01-24 09:16:40 +01:00
Gael Guennebaud
35bf99c63e bug #1376: add missing assertion on size mismatch with compound assignment operators (e.g., mat += mat.col(j))
(grafted from ba3f977946
)
2017-01-23 22:06:08 +01:00
Gael Guennebaud
f9b8729597 bug #1382: move using std::size_t/ptrdiff_t to Eigen's namespace (still better than the global namespace!)
(grafted from b0db4eff36
)
2017-01-23 22:03:57 +01:00
Gael Guennebaud
4b2e7f26aa Add std:: namespace prefix to all (hopefully) instances if size_t/ptrdfiff_t 2017-01-23 22:02:53 +01:00
Gael Guennebaud
5202bc92e6 Use Index instead of size_t
(grafted from 4b607b5692
)
2017-01-23 22:00:33 +01:00
Gael Guennebaud
9d83411cc4 bug #1379: fix compilation in sparse*diagonal*dense with openmp
(grafted from 0fe278f7be
)
2017-01-21 23:27:01 +01:00
Gael Guennebaud
556c03a09d bug #1378: fix doc (DiagonalIndex vs Diagonal)
(grafted from 22a172751e
)
2017-01-21 22:09:59 +01:00
Gael Guennebaud
ce463b9fa4 Added tag 3.3.2 for changeset 477d1e8192 2017-01-18 15:06:46 +01:00
Gael Guennebaud
477d1e8192 Bump to 3.3.2 2017-01-18 15:06:40 +01:00
Gael Guennebaud
0eaff8fdf2 Defer set-to-zero in triangular = product so that no aliasing issue occur in the common:
A.triangularView() = B*A.sefladjointView()*B.adjoint()
case that used to work in 3.2.
(grafted from 655ba783f8
)
2017-01-17 18:03:35 +01:00
Gael Guennebaud
582c96691b Fix typo 2017-01-16 13:36:56 +01:00
Gael Guennebaud
0b22158d9f Add missing doc of SparseView
(grafted from 831fffe874
)
2017-01-06 18:01:29 +01:00
Gael Guennebaud
dafdb0d8a8 MSVC 2015 has all we want about c++11 and MSVC 2017 fails on binder1st/binder2nd
(grafted from e383d6159a
)
2017-01-06 15:44:13 +01:00
Gael Guennebaud
1d1686c62b Convert integers to real numbers when computing relative L2 error
(grafted from f3f026c9aa
)
2017-01-05 13:36:08 +01:00
Gael Guennebaud
ad95b924d0 Fix and workaround several doxygen issues/warnings
(grafted from 2299717fd5
)
2017-01-04 23:27:33 +01:00
Gael Guennebaud
9499684320 Add doc for sparse triangular solve functions
(grafted from ee6f7f6c0c
)
2017-01-04 23:10:36 +01:00
Gael Guennebaud
5b6a31626b Add missing snippet files.
(grafted from 5165de97a4
)
2017-01-04 23:08:27 +01:00
Gael Guennebaud
bc3fee2d8e bug #1336: workaround doxygen failing to include numerous members of MatriBase in Matrix
(grafted from a0a36ad0ef
)
2017-01-04 22:02:39 +01:00
Gael Guennebaud
eaa9223277 Document selfadjointView
(grafted from 29a1a58113
)
2017-01-04 22:01:50 +01:00
Gael Guennebaud
c9ba1165e7 bug #1336: fix doxygen issue regarding EIGEN_CWISE_BINARY_RETURN_TYPE
(grafted from a5ebc92f8d
)
2017-01-04 18:21:44 +01:00
Gael Guennebaud
dd2d5d67ff bug #1370: add doc for StorageIndex
(grafted from 8702562177
)
2017-01-03 11:25:41 +01:00
Gael Guennebaud
404322b64f bug #1370: rename _Index to _StorageIndex in SparseMatrix, and add a warning in the doc regarding the 3.2 to 3.3 change of SparseMatrix::Index
(grafted from 575c078759
)
2017-01-03 11:19:14 +01:00
Marco Falke
ce37bae2cd doc: Fix trivial typo in AsciiQuickReference.txt
* * *
fixup!
(grafted from 4ebf69394d
)
2017-01-01 13:25:48 +00:00
Gael Guennebaud
3900dbc341 Make sure that traits<CwiseBinaryOp>::Flags reports the correct storage order so that methods like .outerSize()/.innerSize() work properly.
(grafted from d32a43e33a
)
2016-12-27 16:35:45 +01:00
Gael Guennebaud
5f586c2bd0 Add missing .outer() member to iterators of evaluators of cwise sparse binary expression
(grafted from 7136267461
)
2016-12-27 16:34:30 +01:00
Gael Guennebaud
215f88a417 Fix check of storage order mismatch for "sparse cwiseop sparse".
(grafted from fe0ee72390
)
2016-12-27 16:33:19 +01:00
Gael Guennebaud
2257f40f4a Merged in angelos_m/eigen/3.3 (pull request PR-269)
Remove superfluous const's (can cause warnings on some Intel compilers)
2016-12-21 08:53:16 +01:00
Gael Guennebaud
9e0fa0ef6d Fix bug #1367: compilation fix for gcc 4.1!
(grafted from 94e8d8902f
)
2016-12-20 22:17:01 +01:00
Gael Guennebaud
0fddbf3dc7 Add transpose, adjoint, conjugate methods to SelfAdjointView (useful to write generic code)
(grafted from 684cfc762d
)
2016-12-20 16:33:53 +01:00
Gael Guennebaud
eda635bd58 Make sure that HyperPlane::transform manitains a unit normal vector in the Affine case.
(grafted from f5d644b415
)
2016-12-20 09:35:00 +01:00
Benoit Jacob
26197bb467 Use 32 registers on ARM64 2016-12-19 13:44:46 -05:00
Gael Guennebaud
772e59d475 bug #1360: fix sign issue with pmull on altivec
(grafted from 8c0e701504
)
2016-12-18 22:13:19 +00:00
Gael Guennebaud
e8f83cbb5d Fix unused warning
(grafted from fc94258e77
)
2016-12-18 22:11:48 +00:00
Gael Guennebaud
dce584d799 bug #1363: fix mingw's ABI issue
(grafted from 5d00fdf0e8
)
2016-12-15 11:58:31 +01:00
Gael Guennebaud
0bcef9557d bug #1358: fix compilation for sparse += sparse.selfadjointView();
(grafted from 11b492e993
)
2016-12-14 17:53:47 +01:00
Gael Guennebaud
2b3c876b2a bug #1359: fix compilation of col_major_sparse.row() *= scalar
(used to work in 3.2.9 though the expression is not really writable)
(grafted from e67397bfa7
)
2016-12-14 17:05:26 +01:00
Gael Guennebaud
a05f6aad0e bug #1359: fix sparse /=scalar and *=scalar implementation.
InnerIterators must be obtained from an evaluator.
(grafted from 98d7458275
)
2016-12-14 17:03:13 +01:00
Gael Guennebaud
59187285e1 bug #1361: fix compilation issue in mat=perm.inverse()
(grafted from c817ce3ba3
)
2016-12-13 23:10:27 +01:00
Angelos Mantzaflaris
1dd074ea7e Merged eigen/eigen/3.3 into 3.3 2016-12-07 01:01:50 +01:00
Angelos Mantzaflaris
24fa7a01bd merge 2016-12-07 00:43:55 +01:00
Angelos Mantzaflaris
e236d3443c Remove superfluous const's (can cause warnings on some Intel compilers) 2016-12-07 00:37:48 +01:00
Gael Guennebaud
4ec8833220 Added tag 3.3.1 for changeset dd3685cc6a 2016-12-06 11:44:02 +01:00
Gael Guennebaud
dd3685cc6a Bump to 3.3.1 2016-12-06 11:43:58 +01:00
Gael Guennebaud
487a6e6515 Explain how to choose your favorite Eigen version
(grafted from 0c4d05b009
)
2016-12-06 11:34:06 +01:00
Silvio Traversaro
75f0b8aae3 Added relocatable cmake support also for CMake before 3.0 and after 2.8.8
(grafted from e049a2a72a
)
2016-12-06 10:37:34 +01:00
Gael Guennebaud
23aca8a586 Optimize SparseLU::solve for rhs vectors
(grafted from 8640ffac65
)
2016-12-05 15:41:14 +01:00
Gael Guennebaud
28bf2bf070 remove temporary in SparseLU::solve
(grafted from 62acd67903
)
2016-12-05 15:11:57 +01:00
Silvio Traversaro
0164f4c682 Make CMake config file relocatable
(grafted from 18481b518f
)
2016-12-05 10:39:52 +01:00
Gael Guennebaud
bbff608a42 Merged in angelos_m/eigen/3.3 (pull request PR-264)
add explicit template to numext::abs2 and fix signed/unsigned warning
2016-12-05 21:56:01 +00:00
Gael Guennebaud
ea56d2ff2c Fix memory leak in Ref<Sparse>
(grafted from a6b971e291
)
2016-12-05 16:59:30 +01:00
Gael Guennebaud
a4c8701e9a bug #1356: fix calls to evaluator::coeffRef(0,0) to get the address of the destination
by adding a dstDataPtr() member to the kernel. This fixes undefined behavior if dst is empty (nullptr).
(grafted from 0db6d5b3f4
)
2016-12-05 15:08:09 +01:00
Gael Guennebaud
a9bb9796e0 Ease compiler job to generate clean and efficient code in mat*vec.
(grafted from 66f65ccc36
)
2016-12-02 22:41:26 +01:00
Gael Guennebaud
449883be74 Operators += and -= do not resize!
(grafted from fe696022ec
)
2016-12-02 22:40:25 +01:00
Angelos Mantzaflaris
0a08d4c60b use numext::abs 2016-12-02 11:48:06 +01:00
Angelos Mantzaflaris
4086187e49 1. Add explicit template to abs2 (resolves deduction for some arithmetic types)
2. Avoid signed-unsigned conversion in comparison (warning in case Scalar is unsigned)
2016-12-02 11:39:18 +01:00
Christoph Hertzberg
91864f85d3 bug #1355: Fixed wrong line-endings on two files
(grafted from 22f7d398e2
)
2016-12-02 11:22:05 +01:00
Gael Guennebaud
c3597106ab Merged in angelos_m/eigen/3.3 (pull request PR-263)
fix two warnings(unused typedef, unused variable) and a typo
2016-12-02 09:02:39 +00:00
Gael Guennebaud
aed1d6597f Clean up SparseCore module regarding ReverseInnerIterator
(grafted from 27873008d4
)
2016-12-01 21:55:10 +01:00
Angelos Mantzaflaris
b6f04a2dd4 typo UIntPtr 2016-12-01 21:25:58 +01:00
Angelos Mantzaflaris
a9aa3bcf50 fix two warnings(unused typedef, unused variable) and a typo 2016-12-01 21:23:43 +01:00
Gael Guennebaud
32b8da66e3 fix member order
(grafted from 181138a1cb
)
2016-12-01 17:06:20 +01:00
Gael Guennebaud
eb94179ea3 Merged in sergiu/eigen/cmake-imported-target (pull request PR-257)
CMake imported target (take #2)
2016-12-01 15:13:48 +00:00
Gael Guennebaud
52a7386aef Fix misleading-indentation warnings.
(grafted from 037b46762d
)
2016-12-01 16:05:42 +01:00
Gael Guennebaud
8cada1d894 Fix slection of product implementation for dynamic size matrices with fixed max size.
(grafted from 8df272af88
)
2016-11-30 22:21:33 +01:00
Gael Guennebaud
6e4a664c42 Fix a performance regression in (mat*mat)*vec for which mat*mat was evaluated multiple times.
(grafted from c927af60ed
)
2016-11-30 17:59:13 +01:00
Gael Guennebaud
1cd1a96d56 bug #1351: fix compilation of random with old compilers
(grafted from ab4ef5e66e
)
2016-11-30 17:37:53 +01:00
Sergiu Deitsch
86ab00cdcf cmake: remove architecture dependency from Eigen3ConfigVersion.cmake
Also, install Eigen3*.cmake under $prefix/share/eigen3/cmake by default.
2016-11-30 15:46:46 +01:00
Sergiu Deitsch
65f09be8d2 doc: mention the NO_MODULE option and target availability 2016-11-30 15:41:38 +01:00
Gael Guennebaud
400d756b82 bug #1348: Document EIGEN_MAX_ALIGN_BYTES and EIGEN_MAX_STATIC_ALIGN_BYTES,
and reflect in the doc that EIGEN_DONT_ALIGN* are deprecated.
(grafted from 21d0286d81
)
2016-11-23 22:15:03 +01:00
Gael Guennebaud
9d31798a84 update cdash project for 3.3 2016-11-23 14:13:08 +01:00
Gael Guennebaud
723ed92e0e Fix compilation with gcc and old ABI version
(grafted from e340866c81
)
2016-11-23 14:04:57 +01:00
Gael Guennebaud
0a7de0b273 Fix compilation issue with MSVC:
MSVC always messes up with shadowed template arguments, for instance in:
  struct B { typedef float T; }
  template<typename T> struct A : B {
    T g;
  };
The type of A<double>::g will be float and not double.
(grafted from a91de27e98
)
2016-11-23 12:24:48 +01:00
Gael Guennebaud
d6b9bc1ccd Optimize predux<Packet8f> (AVX)
(grafted from 74637fa4e3
)
2016-11-22 21:57:52 +01:00
Gael Guennebaud
0eff51e2ed Disable usage of SSE3 _mm_hadd_ps that is extremely slow.
(grafted from 178c084856
)
2016-11-22 21:53:14 +01:00
Gael Guennebaud
1b7dd46d94 Optimize predux<Packet4d> (AVX)
(grafted from 7dd894e40e
)
2016-11-22 21:41:30 +01:00
Gael Guennebaud
b2eb1bf3dc Disable usage of SSE3 haddpd that is extremely slow.
(grafted from f3fb0a1940
)
2016-11-22 16:58:31 +01:00
Gael Guennebaud
fe48c25682 Revert vec/y to vec*(1/y) in row-major TRSM:
- div is extremely costly
- this is consistent with the column-major case
- this is consistent with all other BLAS implementations
(grafted from eb621413c1
)
2016-12-06 15:04:50 +01:00
Gael Guennebaud
0ba6da3470 Fix BLAS backend for symmetric rank K updates.
(grafted from 8365c2c941
)
2016-12-06 14:47:09 +01:00
Sergiu Deitsch
a287140f72 cmake: added Eigen3::Eigen imported target 2016-11-22 12:25:06 +01:00
Gael Guennebaud
4d89ec8a00 Fix regression in assigment of sparse block to spasre block.
(grafted from 6a84246a6a
)
2016-11-21 21:46:42 +01:00
Chun Wang
441760f239 Workaround for error in VS2012 with /clr
(grafted from 0d0948c3b9
)
2016-11-17 17:54:27 -05:00
Gael Guennebaud
664162fb8a Fix compilation issue in mat = permutation (regression introduced in 8193ffb3d3
)
(grafted from 465ede0f20
)
2016-11-20 09:41:37 +01:00
Gael Guennebaud
aa3c761002 bug #1343: fix compilation regression in mat+=selfadjoint_view.
Generic EigenBase2EigenBase assignment was incomplete.
(grafted from 8193ffb3d3
)
2016-11-18 10:17:34 +01:00
Gael Guennebaud
94f2cfc9c7 bug #1343: fix compilation regression in array = matrix_product
(grafted from cebff7e3a2
)
2016-11-18 10:09:33 +01:00
Konstantinos Margaritis
4a13d79df6 replace sizeof(Packet) with PacketSize else it breaks for ZVector.Packet4f
(grafted from a1d5c503fa
)
2016-11-17 13:27:45 -05:00
Konstantinos Margaritis
463176cc44 implement float/std::complex<float> for ZVector as well, minor fixes to ZVector
(grafted from 672aa97d4d
)
2016-11-17 13:27:33 -05:00
Gael Guennebaud
5aab97fba6 Optimize sparse<bool> && sparse<bool> to use the same path as for coeff-wise products.
(grafted from 0ee92aa38e
)
2016-11-14 18:47:41 +01:00
Gael Guennebaud
89abc6806d bug #426: move operator && and || to MatrixBase and SparseMatrixBase.
(grafted from 2e334f5da0
)
2016-11-14 18:47:02 +01:00
Niels Ole Salscheider
baf793ebaa Make sure not to call numext::maxi on expression templates
(grafted from 51fef87408
)
2016-11-12 12:20:57 +01:00
Gael Guennebaud
b4ddafcfac Fix regression in SparseMatrix::ReverseInnerIterator
(grafted from eedb87f4ba
)
2016-11-14 14:05:53 +01:00
Gael Guennebaud
1079967710 Added tag 3.3.0 for changeset eeac81b8c0 2016-11-10 13:57:29 +01:00
331 changed files with 9399 additions and 3328 deletions

View File

@@ -13,7 +13,7 @@ core
core.*
*.bak
*~
build*
*build*
*.moc.*
*.moc
ui_*

View File

@@ -41,10 +41,13 @@ string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen_minor_
set(EIGEN_MINOR_VERSION "${CMAKE_MATCH_1}")
set(EIGEN_VERSION_NUMBER ${EIGEN_WORLD_VERSION}.${EIGEN_MAJOR_VERSION}.${EIGEN_MINOR_VERSION})
# if the mercurial program is absent, this will leave the EIGEN_HG_CHANGESET string empty,
# but won't stop CMake.
execute_process(COMMAND hg tip -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_HGTIP_OUTPUT)
execute_process(COMMAND hg branch -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_BRANCH_OUTPUT)
# if we are not in a mercurial clone
if(IS_DIRECTORY ${CMAKE_SOURCE_DIR}/.hg)
# if the mercurial program is absent or this will leave the EIGEN_HG_CHANGESET string empty,
# but won't stop CMake.
execute_process(COMMAND hg tip -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_HGTIP_OUTPUT)
execute_process(COMMAND hg branch -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_BRANCH_OUTPUT)
endif()
# if this is the default (aka development) branch, extract the mercurial changeset number from the hg tip output...
if(EIGEN_BRANCH_OUTPUT MATCHES "default")
@@ -64,6 +67,33 @@ include(GNUInstallDirs)
set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
macro(ei_add_cxx_compiler_flag FLAG)
string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
if(COMPILER_SUPPORT_${SFLAG})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
endif()
endmacro(ei_add_cxx_compiler_flag)
check_cxx_compiler_flag("-std=c++11" EIGEN_COMPILER_SUPPORT_CPP11)
if(EIGEN_TEST_CXX11)
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_EXTENSIONS OFF)
if(EIGEN_COMPILER_SUPPORT_CPP11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
endif()
else()
#set(CMAKE_CXX_STANDARD 03)
#set(CMAKE_CXX_EXTENSIONS OFF)
ei_add_cxx_compiler_flag("-std=c++03")
endif()
#############################################################################
# find how to link to the standard libraries #
#############################################################################
@@ -115,15 +145,6 @@ endif()
set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
macro(ei_add_cxx_compiler_flag FLAG)
string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
if(COMPILER_SUPPORT_${SFLAG})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
endif()
endmacro(ei_add_cxx_compiler_flag)
if(NOT MSVC)
# We assume that other compilers are partly compatible with GNUCC
@@ -359,8 +380,6 @@ if(EIGEN_TEST_NO_EXCEPTIONS)
message(STATUS "Disabling exceptions in tests/examples")
endif()
option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
set(EIGEN_CUDA_COMPUTE_ARCH 30 CACHE STRING "The CUDA compute architecture level to target when compiling CUDA code")
include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
@@ -380,7 +399,7 @@ else()
)
endif()
set(CMAKEPACKAGE_INSTALL_DIR
"${CMAKE_INSTALL_LIBDIR}/cmake/eigen3"
"${CMAKE_INSTALL_DATADIR}/eigen3/cmake"
CACHE PATH "The directory relative to CMAKE_PREFIX_PATH where Eigen3Config.cmake is installed"
)
set(PKGCONFIG_INSTALL_DIR
@@ -416,16 +435,15 @@ add_subdirectory(Eigen)
add_subdirectory(doc EXCLUDE_FROM_ALL)
include(EigenConfigureTesting)
option(BUILD_TESTING "Enable creation of Eigen tests." ON)
if(BUILD_TESTING)
include(EigenConfigureTesting)
# fixme, not sure this line is still needed:
enable_testing() # must be called from the root CMakeLists, see man page
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
else()
add_subdirectory(test EXCLUDE_FROM_ALL)
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
else()
add_subdirectory(test EXCLUDE_FROM_ALL)
endif()
endif()
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
@@ -461,7 +479,9 @@ endif(NOT WIN32)
configure_file(scripts/cdashtesting.cmake.in cdashtesting.cmake @ONLY)
ei_testing_print_summary()
if(BUILD_TESTING)
ei_testing_print_summary()
endif()
message(STATUS "")
message(STATUS "Configured Eigen ${EIGEN_VERSION_NUMBER}")
@@ -507,18 +527,89 @@ set ( EIGEN_VERSION_MINOR ${EIGEN_MAJOR_VERSION} )
set ( EIGEN_VERSION_PATCH ${EIGEN_MINOR_VERSION} )
set ( EIGEN_DEFINITIONS "")
set ( EIGEN_INCLUDE_DIR "${CMAKE_INSTALL_PREFIX}/${INCLUDE_INSTALL_DIR}" )
set ( EIGEN_INCLUDE_DIRS ${EIGEN_INCLUDE_DIR} )
set ( EIGEN_ROOT_DIR ${CMAKE_INSTALL_PREFIX} )
configure_file ( ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
@ONLY ESCAPE_QUOTES
)
# Interface libraries require at least CMake 3.0
if (NOT CMAKE_VERSION VERSION_LESS 3.0)
include (CMakePackageConfigHelpers)
# Imported target support
add_library (eigen INTERFACE)
target_compile_definitions (eigen INTERFACE ${EIGEN_DEFINITIONS})
target_include_directories (eigen INTERFACE
$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
$<INSTALL_INTERFACE:${INCLUDE_INSTALL_DIR}>
)
# Export as title case Eigen
set_target_properties (eigen PROPERTIES EXPORT_NAME Eigen)
install (TARGETS eigen EXPORT Eigen3Targets)
configure_package_config_file (
${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
PATH_VARS EIGEN_INCLUDE_DIR EIGEN_ROOT_DIR
INSTALL_DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
NO_CHECK_REQUIRED_COMPONENTS_MACRO # Eigen does not provide components
)
# Remove CMAKE_SIZEOF_VOID_P from Eigen3ConfigVersion.cmake since Eigen does
# not depend on architecture specific settings or libraries. More
# specifically, an Eigen3Config.cmake generated from a 64 bit target can be
# used for 32 bit targets as well (and vice versa).
set (_Eigen3_CMAKE_SIZEOF_VOID_P ${CMAKE_SIZEOF_VOID_P})
unset (CMAKE_SIZEOF_VOID_P)
write_basic_package_version_file (Eigen3ConfigVersion.cmake
VERSION ${EIGEN_VERSION_NUMBER}
COMPATIBILITY SameMajorVersion)
set (CMAKE_SIZEOF_VOID_P ${_Eigen3_CMAKE_SIZEOF_VOID_P})
# The Eigen target will be located in the Eigen3 namespace. Other CMake
# targets can refer to it using Eigen3::Eigen.
export (TARGETS eigen NAMESPACE Eigen3:: FILE Eigen3Targets.cmake)
# Export Eigen3 package to CMake registry such that it can be easily found by
# CMake even if it has not been installed to a standard directory.
export (PACKAGE Eigen3)
install (EXPORT Eigen3Targets NAMESPACE Eigen3:: DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
else (NOT CMAKE_VERSION VERSION_LESS 3.0)
# Fallback to legacy Eigen3Config.cmake without the imported target
# If CMakePackageConfigHelpers module is available (CMake >= 2.8.8)
# create a relocatable Config file, otherwise leave the hardcoded paths
include(CMakePackageConfigHelpers OPTIONAL RESULT_VARIABLE CPCH_PATH)
if(CPCH_PATH)
configure_package_config_file (
${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3ConfigLegacy.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
PATH_VARS EIGEN_INCLUDE_DIR EIGEN_ROOT_DIR
INSTALL_DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
NO_CHECK_REQUIRED_COMPONENTS_MACRO # Eigen does not provide components
)
else()
# The PACKAGE_* variables are defined by the configure_package_config_file
# but without it we define them manually to the hardcoded paths
set(PACKAGE_INIT "")
set(PACKAGE_EIGEN_INCLUDE_DIR ${EIGEN_INCLUDE_DIR})
set(PACKAGE_EIGEN_ROOT_DIR ${EIGEN_ROOT_DIR})
configure_file ( ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3ConfigLegacy.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
@ONLY ESCAPE_QUOTES )
endif()
write_basic_package_version_file( Eigen3ConfigVersion.cmake
VERSION ${EIGEN_VERSION_NUMBER}
COMPATIBILITY SameMajorVersion )
endif (NOT CMAKE_VERSION VERSION_LESS 3.0)
install ( FILES ${CMAKE_CURRENT_SOURCE_DIR}/cmake/UseEigen3.cmake
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
)
${CMAKE_CURRENT_BINARY_DIR}/Eigen3ConfigVersion.cmake
DESTINATION ${CMAKEPACKAGE_INSTALL_DIR} )
# Add uninstall target
add_custom_target ( uninstall

View File

@@ -4,14 +4,10 @@
## # The following are required to uses Dart and the Cdash dashboard
## ENABLE_TESTING()
## INCLUDE(CTest)
set(CTEST_PROJECT_NAME "Eigen")
set(CTEST_PROJECT_NAME "Eigen 3.3")
set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
set(CTEST_DROP_METHOD "http")
set(CTEST_DROP_SITE "manao.inria.fr")
set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen+3.3")
set(CTEST_DROP_SITE_CDASH TRUE)
set(CTEST_PROJECT_SUBPROJECTS
Official
Unsupported
)

View File

@@ -1,3 +1,4 @@
set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "2000")
set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS "2000")
list(APPEND CTEST_CUSTOM_ERROR_EXCEPTION @EIGEN_CTEST_ERROR_EXCEPTION@)

View File

@@ -9,6 +9,7 @@
#define EIGEN_CHOLESKY_MODULE_H
#include "Core"
#include "Jacobi"
#include "src/Core/util/DisableStupidWarnings.h"
@@ -31,7 +32,11 @@
#include "src/Cholesky/LLT.h"
#include "src/Cholesky/LDLT.h"
#ifdef EIGEN_USE_LAPACKE
#ifdef EIGEN_USE_MKL
#include "mkl_lapacke.h"
#else
#include "src/misc/lapacke.h"
#endif
#include "src/Cholesky/LLT_LAPACKE.h"
#endif

View File

@@ -14,6 +14,22 @@
// first thing Eigen does: stop the compiler from committing suicide
#include "src/Core/util/DisableStupidWarnings.h"
#if defined(__CUDACC__) && !defined(EIGEN_NO_CUDA)
#define EIGEN_CUDACC __CUDACC__
#endif
#if defined(__CUDA_ARCH__) && !defined(EIGEN_NO_CUDA)
#define EIGEN_CUDA_ARCH __CUDA_ARCH__
#endif
#if defined(__CUDACC_VER_MAJOR__) && (__CUDACC_VER_MAJOR__ >= 9)
#define EIGEN_CUDACC_VER ((__CUDACC_VER_MAJOR__ * 10000) + (__CUDACC_VER_MINOR__ * 100))
#elif defined(__CUDACC_VER__)
#define EIGEN_CUDACC_VER __CUDACC_VER__
#else
#define EIGEN_CUDACC_VER 0
#endif
// Handle NVCC/CUDA/SYCL
#if defined(__CUDACC__) || defined(__SYCL_DEVICE_ONLY__)
// Do not try asserts on CUDA and SYCL!
@@ -37,9 +53,9 @@
#endif
#define EIGEN_DEVICE_FUNC __host__ __device__
// We need math_functions.hpp to ensure that that EIGEN_USING_STD_MATH macro
// We need cuda_runtime.h to ensure that that EIGEN_USING_STD_MATH macro
// works properly on the device side
#include <math_functions.hpp>
#include <cuda_runtime.h>
#else
#define EIGEN_DEVICE_FUNC
#endif
@@ -155,6 +171,9 @@
#ifdef __AVX512DQ__
#define EIGEN_VECTORIZE_AVX512DQ
#endif
#ifdef __AVX512ER__
#define EIGEN_VECTORIZE_AVX512ER
#endif
#endif
// include files
@@ -229,7 +248,7 @@
#if defined __CUDACC__
#define EIGEN_VECTORIZE_CUDA
#include <vector_types.h>
#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
#if EIGEN_CUDACC_VER >= 70500
#define EIGEN_HAS_CUDA_FP16
#endif
#endif
@@ -321,12 +340,16 @@ inline static const char *SimdInstructionSetsInUse(void) {
#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
#endif
namespace Eigen {
// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
// ensure QNX/QCC support
using std::size_t;
// gcc 4.6.0 wants std:: for ptrdiff_t
using std::ptrdiff_t;
}
/** \defgroup Core_Module Core module
* This is the main module of Eigen providing dense matrix and vector support
* (both fixed and dynamic size) with all the features corresponding to a BLAS library
@@ -348,6 +371,7 @@ using std::ptrdiff_t;
#include "src/Core/MathFunctions.h"
#include "src/Core/GenericPacketMath.h"
#include "src/Core/MathFunctionsImpl.h"
#include "src/Core/arch/Default/ConjHelper.h"
#if defined EIGEN_VECTORIZE_AVX512
#include "src/Core/arch/SSE/PacketMath.h"
@@ -363,6 +387,7 @@ using std::ptrdiff_t;
#include "src/Core/arch/AVX/MathFunctions.h"
#include "src/Core/arch/AVX/Complex.h"
#include "src/Core/arch/AVX/TypeCasting.h"
#include "src/Core/arch/SSE/TypeCasting.h"
#elif defined EIGEN_VECTORIZE_SSE
#include "src/Core/arch/SSE/PacketMath.h"
#include "src/Core/arch/SSE/MathFunctions.h"
@@ -405,6 +430,7 @@ using std::ptrdiff_t;
// on CUDA devices
#include "src/Core/arch/CUDA/Complex.h"
#include "src/Core/IO.h"
#include "src/Core/DenseCoeffsBase.h"
#include "src/Core/DenseBase.h"
#include "src/Core/MatrixBase.h"
@@ -452,7 +478,6 @@ using std::ptrdiff_t;
#include "src/Core/Redux.h"
#include "src/Core/Visitor.h"
#include "src/Core/Fuzzy.h"
#include "src/Core/IO.h"
#include "src/Core/Swap.h"
#include "src/Core/CommaInitializer.h"
#include "src/Core/GeneralProduct.h"

View File

@@ -45,7 +45,11 @@
#include "src/Eigenvalues/GeneralizedEigenSolver.h"
#include "src/Eigenvalues/MatrixBaseEigenvalues.h"
#ifdef EIGEN_USE_LAPACKE
#ifdef EIGEN_USE_MKL
#include "mkl_lapacke.h"
#else
#include "src/misc/lapacke.h"
#endif
#include "src/Eigenvalues/RealSchur_LAPACKE.h"
#include "src/Eigenvalues/ComplexSchur_LAPACKE.h"
#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h"

View File

@@ -28,7 +28,11 @@
#include "src/LU/FullPivLU.h"
#include "src/LU/PartialPivLU.h"
#ifdef EIGEN_USE_LAPACKE
#ifdef EIGEN_USE_MKL
#include "mkl_lapacke.h"
#else
#include "src/misc/lapacke.h"
#endif
#include "src/LU/PartialPivLU_LAPACKE.h"
#endif
#include "src/LU/Determinant.h"

View File

@@ -36,7 +36,11 @@
#include "src/QR/ColPivHouseholderQR.h"
#include "src/QR/CompleteOrthogonalDecomposition.h"
#ifdef EIGEN_USE_LAPACKE
#ifdef EIGEN_USE_MKL
#include "mkl_lapacke.h"
#else
#include "src/misc/lapacke.h"
#endif
#include "src/QR/HouseholderQR_LAPACKE.h"
#include "src/QR/ColPivHouseholderQR_LAPACKE.h"
#endif

View File

@@ -14,7 +14,7 @@
#include "src/Core/util/DisableStupidWarnings.h"
void *qMalloc(size_t size)
void *qMalloc(std::size_t size)
{
return Eigen::internal::aligned_malloc(size);
}
@@ -24,10 +24,10 @@ void qFree(void *ptr)
Eigen::internal::aligned_free(ptr);
}
void *qRealloc(void *ptr, size_t size)
void *qRealloc(void *ptr, std::size_t size)
{
void* newPtr = Eigen::internal::aligned_malloc(size);
memcpy(newPtr, ptr, size);
std::memcpy(newPtr, ptr, size);
Eigen::internal::aligned_free(ptr);
return newPtr;
}

View File

@@ -37,7 +37,11 @@
#include "src/SVD/JacobiSVD.h"
#include "src/SVD/BDCSVD.h"
#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
#ifdef EIGEN_USE_MKL
#include "mkl_lapacke.h"
#else
#include "src/misc/lapacke.h"
#endif
#include "src/SVD/JacobiSVD_LAPACKE.h"
#endif

View File

@@ -25,7 +25,9 @@
#include "SparseCore"
#include "OrderingMethods"
#ifndef EIGEN_MPL2_ONLY
#include "SparseCholesky"
#endif
#include "SparseLU"
#include "SparseQR"
#include "IterativeLinearSolvers"

View File

@@ -14,7 +14,7 @@
#include "Core"
#include <deque>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)

View File

@@ -13,7 +13,7 @@
#include "Core"
#include <list>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)

View File

@@ -14,7 +14,7 @@
#include "Core"
#include <vector>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)

View File

@@ -248,7 +248,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
/** \brief Reports whether previous computation was successful.
*
* \returns \c Success if computation was succesful,
* \c NumericalIssue if the matrix.appears to be negative.
* \c NumericalIssue if the factorization failed because of a zero pivot.
*/
ComputationInfo info() const
{
@@ -305,7 +305,8 @@ template<> struct ldlt_inplace<Lower>
if (size <= 1)
{
transpositions.setIdentity();
if (numext::real(mat.coeff(0,0)) > static_cast<RealScalar>(0) ) sign = PositiveSemiDef;
if(size==0) sign = ZeroSign;
else if (numext::real(mat.coeff(0,0)) > static_cast<RealScalar>(0) ) sign = PositiveSemiDef;
else if (numext::real(mat.coeff(0,0)) < static_cast<RealScalar>(0)) sign = NegativeSemiDef;
else sign = ZeroSign;
return true;
@@ -376,6 +377,8 @@ template<> struct ldlt_inplace<Lower>
if((rs>0) && pivot_is_valid)
A21 /= realAkk;
else if(rs>0)
ret = ret && (A21.array()==Scalar(0)).all();
if(found_zero_pivot && pivot_is_valid) ret = false; // factorization failed
else if(!pivot_is_valid) found_zero_pivot = true;
@@ -568,13 +571,14 @@ void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) cons
// more precisely, use pseudo-inverse of D (see bug 241)
using std::abs;
const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
// as motivated by LAPACK's xGELSS:
// In some previous versions, tolerance was set to the max of 1/highest (or rather numeric_limits::min())
// and the maximal diagonal entry * epsilon as motivated by LAPACK's xGELSS:
// RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
// diagonal element is not well justified and leads to numerical issues in some cases.
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
// Using numeric_limits::min() gives us more robustness to denormals.
RealScalar tolerance = (std::numeric_limits<RealScalar>::min)();
for (Index i = 0; i < vecD.size(); ++i)
{

View File

@@ -24,7 +24,7 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
*
* \tparam _MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
* \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
* The other triangular part won't be read.
* The other triangular part won't be read.
*
* This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
* matrix A such that A = LL^* = U^*U, where L is lower triangular.
@@ -41,14 +41,18 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
* Example: \include LLT_example.cpp
* Output: \verbinclude LLT_example.out
*
* \b Performance: for best performance, it is recommended to use a column-major storage format
* with the Lower triangular part (the default), or, equivalently, a row-major storage format
* with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization
* step, and rank-updates can be up to 3 times slower.
*
* This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
*
* Note that during the decomposition, only the lower (or upper, as defined by _UpLo) triangular part of A is considered.
* Therefore, the strict lower part does not have to store correct values.
*
* \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
*/
/* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
* Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
* the strict lower part does not have to store correct values.
*/
template<typename _MatrixType, int _UpLo> class LLT
{
public:
@@ -146,7 +150,7 @@ template<typename _MatrixType, int _UpLo> class LLT
}
template<typename Derived>
void solveInPlace(MatrixBase<Derived> &bAndX) const;
void solveInPlace(const MatrixBase<Derived> &bAndX) const;
template<typename InputType>
LLT& compute(const EigenBase<InputType>& matrix);
@@ -177,7 +181,7 @@ template<typename _MatrixType, int _UpLo> class LLT
/** \brief Reports whether previous computation was successful.
*
* \returns \c Success if computation was succesful,
* \c NumericalIssue if the matrix.appears to be negative.
* \c NumericalIssue if the matrix.appears not to be positive definite.
*/
ComputationInfo info() const
{
@@ -425,7 +429,8 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>
eigen_assert(a.rows()==a.cols());
const Index size = a.rows();
m_matrix.resize(size, size);
m_matrix = a.derived();
if (!internal::is_same_dense(m_matrix, a.derived()))
m_matrix = a.derived();
// Compute matrix L1 norm = max abs column sum.
m_l1_norm = RealScalar(0);
@@ -485,11 +490,14 @@ void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
*
* This version avoids a copy when the right hand side matrix b is not needed anymore.
*
* \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
* This function will const_cast it, so constness isn't honored here.
*
* \sa LLT::solve(), MatrixBase::llt()
*/
template<typename MatrixType, int _UpLo>
template<typename Derived>
void LLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
void LLT<MatrixType,_UpLo>::solveInPlace(const MatrixBase<Derived> &bAndX) const
{
eigen_assert(m_isInitialized && "LLT is not initialized.");
eigen_assert(m_matrix.rows()==bAndX.rows());

View File

@@ -153,8 +153,6 @@ class Array
: Base(std::move(other))
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
}
EIGEN_DEVICE_FUNC
Array& operator=(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
@@ -231,10 +229,16 @@ class Array
: Base(other)
{ }
private:
struct PrivateType {};
public:
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other,
typename internal::enable_if<internal::is_convertible<typename OtherDerived::Scalar,Scalar>::value,
PrivateType>::type = PrivateType())
: Base(other.derived())
{ }

View File

@@ -175,7 +175,7 @@ template<typename Derived> class ArrayBase
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -188,7 +188,7 @@ ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -201,7 +201,7 @@ ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -214,7 +214,7 @@ ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar,typename OtherDerived::Scalar>());

View File

@@ -32,7 +32,8 @@ struct traits<ArrayWrapper<ExpressionType> >
// Let's remove NestByRefBit
enum {
Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
Flags = Flags0 & ~NestByRefBit
LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
};
};
}
@@ -129,7 +130,8 @@ struct traits<MatrixWrapper<ExpressionType> >
// Let's remove NestByRefBit
enum {
Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
Flags = Flags0 & ~NestByRefBit
LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
};
};
}

View File

@@ -39,7 +39,7 @@ public:
enum {
DstAlignment = DstEvaluator::Alignment,
SrcAlignment = SrcEvaluator::Alignment,
DstHasDirectAccess = DstFlags & DirectAccessBit,
DstHasDirectAccess = (DstFlags & DirectAccessBit) == DirectAccessBit,
JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
};
@@ -83,7 +83,7 @@ private:
&& int(OuterStride)!=Dynamic && int(OuterStride)%int(InnerPacketSize)==0
&& (EIGEN_UNALIGNED_VECTORIZE || int(JointAlignment)>=int(InnerRequiredAlignment)),
MayLinearize = bool(StorageOrdersAgree) && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
MayLinearVectorize = bool(MightVectorize) && MayLinearize && DstHasDirectAccess
MayLinearVectorize = bool(MightVectorize) && bool(MayLinearize) && bool(DstHasDirectAccess)
&& (EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)) || MaxSizeAtCompileTime == Dynamic),
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
so it's only good for large enough sizes. */
@@ -407,7 +407,7 @@ struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
: int(Kernel::AssignmentTraits::DstAlignment),
srcAlignment = Kernel::AssignmentTraits::JointAlignment
};
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(&kernel.dstEvaluator().coeffRef(0), size);
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(kernel.dstDataPtr(), size);
const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
unaligned_dense_assignment_loop<dstIsAligned!=0>::run(kernel, 0, alignedStart);
@@ -515,7 +515,7 @@ struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
template<typename Kernel>
struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::Scalar Scalar;
typedef typename Kernel::PacketType PacketType;
@@ -527,7 +527,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
dstAlignment = alignable ? int(requestedAlignment)
: int(Kernel::AssignmentTraits::DstAlignment)
};
const Scalar *dst_ptr = &kernel.dstEvaluator().coeffRef(0,0);
const Scalar *dst_ptr = kernel.dstDataPtr();
if((!bool(dstIsAligned)) && (UIntPtr(dst_ptr) % sizeof(Scalar))>0)
{
// the pointer is not aligend-on scalar, so alignment is not possible
@@ -563,7 +563,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
template<typename Kernel>
struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, InnerUnrolling>
{
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
typedef typename Kernel::PacketType PacketType;
@@ -683,6 +683,11 @@ public:
: int(DstEvaluatorType::Flags)&RowMajorBit ? inner
: outer;
}
EIGEN_DEVICE_FUNC const Scalar* dstDataPtr() const
{
return m_dstExpr.data();
}
protected:
DstEvaluatorType& m_dst;
@@ -696,6 +701,26 @@ protected:
* Part 5 : Entry point for dense rectangular assignment
***************************************************************************/
template<typename DstXprType,typename SrcXprType, typename Functor>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const Functor &/*func*/)
{
EIGEN_ONLY_USED_FOR_DEBUG(dst);
EIGEN_ONLY_USED_FOR_DEBUG(src);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
}
template<typename DstXprType,typename SrcXprType, typename T1, typename T2>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const internal::assign_op<T1,T2> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if(((dst.rows()!=dstRows) || (dst.cols()!=dstCols)))
dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == dstRows && dst.cols() == dstCols);
}
template<typename DstXprType, typename SrcXprType, typename Functor>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
{
@@ -706,10 +731,7 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType
// NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
// we need to resize the destination after the source evaluator has been created.
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
resize_if_allowed(dst, src, func);
DstEvaluatorType dstEvaluator(dst);
@@ -876,6 +898,34 @@ struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Weak>
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.evalTo(dst);
}
// NOTE The following two functions are templated to avoid their instanciation if not needed
// This is needed because some expressions supports evalTo only and/or have 'void' as scalar type.
template<typename SrcScalarType>
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.addTo(dst);
}
template<typename SrcScalarType>
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.subTo(dst);
}
};
} // namespace internal

View File

@@ -84,7 +84,8 @@ class vml_assign_traits
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>, \
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) { \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \
resize_if_allowed(dst, src, func); \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \
VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \
@@ -144,7 +145,8 @@ EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \
typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \
const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) { \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \
resize_if_allowed(dst, src, func); \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other); \
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \

View File

@@ -160,7 +160,7 @@ rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm, const Deco
{
typedef typename Decomposition::RealScalar RealScalar;
eigen_assert(dec.rows() == dec.cols());
if (dec.rows() == 0) return RealScalar(1);
if (dec.rows() == 0) return NumTraits<RealScalar>::infinity();
if (matrix_norm == RealScalar(0)) return RealScalar(0);
if (dec.rows() == 1) return RealScalar(1);
const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);

View File

@@ -977,7 +977,7 @@ struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
OuterStrideAtCompileTime = HasSameStorageOrderAsArgType
? int(outer_stride_at_compile_time<ArgType>::ret)
: int(inner_stride_at_compile_time<ArgType>::ret),
MaskPacketAccessBit = (InnerStrideAtCompileTime == 1) ? PacketAccessBit : 0,
MaskPacketAccessBit = (InnerStrideAtCompileTime == 1 || HasSameStorageOrderAsArgType) ? PacketAccessBit : 0,
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (evaluator<ArgType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,
FlagsRowMajorBit = XprType::Flags&RowMajorBit,
@@ -987,7 +987,9 @@ struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit,
PacketAlignment = unpacket_traits<PacketScalar>::alignment,
Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0,
Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic)
&& (OuterStrideAtCompileTime!=0)
&& (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0,
Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ArgType>::Alignment, Alignment0)
};
typedef block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> block_evaluator_type;
@@ -1018,14 +1020,16 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa
EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& block)
: m_argImpl(block.nestedExpression()),
m_startRow(block.startRow()),
m_startCol(block.startCol())
m_startCol(block.startCol()),
m_linear_offset(InnerPanel?(XprType::IsRowMajor ? block.startRow()*block.cols() : block.startCol()*block.rows()):0)
{ }
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum {
RowsAtCompileTime = XprType::RowsAtCompileTime
RowsAtCompileTime = XprType::RowsAtCompileTime,
ForwardLinearAccess = InnerPanel && bool(evaluator<ArgType>::Flags&LinearAccessBit)
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -1037,7 +1041,10 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
CoeffReturnType coeff(Index index) const
{
return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
if (ForwardLinearAccess)
return m_argImpl.coeff(m_linear_offset.value() + index);
else
return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -1049,7 +1056,10 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
Scalar& coeffRef(Index index)
{
return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
if (ForwardLinearAccess)
return m_argImpl.coeffRef(m_linear_offset.value() + index);
else
return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
}
template<int LoadMode, typename PacketType>
@@ -1063,8 +1073,11 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa
EIGEN_STRONG_INLINE
PacketType packet(Index index) const
{
return packet<LoadMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
RowsAtCompileTime == 1 ? index : 0);
if (ForwardLinearAccess)
return m_argImpl.template packet<LoadMode,PacketType>(m_linear_offset.value() + index);
else
return packet<LoadMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
RowsAtCompileTime == 1 ? index : 0);
}
template<int StoreMode, typename PacketType>
@@ -1078,15 +1091,19 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa
EIGEN_STRONG_INLINE
void writePacket(Index index, const PacketType& x)
{
return writePacket<StoreMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
RowsAtCompileTime == 1 ? index : 0,
x);
if (ForwardLinearAccess)
return m_argImpl.template writePacket<StoreMode,PacketType>(m_linear_offset.value() + index, x);
else
return writePacket<StoreMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
RowsAtCompileTime == 1 ? index : 0,
x);
}
protected:
evaluator<ArgType> m_argImpl;
const variable_if_dynamic<Index, (ArgType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
const variable_if_dynamic<Index, (ArgType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
const variable_if_dynamic<Index, InnerPanel ? Dynamic : 0> m_linear_offset;
};
// TODO: This evaluator does not actually use the child evaluator;
@@ -1556,9 +1573,7 @@ struct evaluator<Diagonal<ArgType, DiagIndex> >
{ }
typedef typename XprType::Scalar Scalar;
// FIXME having to check whether ArgType is sparse here i not very nice.
typedef typename internal::conditional<!internal::is_same<typename ArgType::StorageKind,Sparse>::value,
typename XprType::CoeffReturnType,Scalar>::type CoeffReturnType;
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
CoeffReturnType coeff(Index row, Index) const

View File

@@ -46,7 +46,7 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
typedef typename remove_reference<LhsNested>::type _LhsNested;
typedef typename remove_reference<RhsNested>::type _RhsNested;
enum {
Flags = _LhsNested::Flags & RowMajorBit
Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind,typename traits<Rhs>::StorageKind,_LhsNested::Flags & RowMajorBit,_RhsNested::Flags & RowMajorBit>::value
};
};
} // end namespace internal
@@ -84,6 +84,7 @@ class CwiseBinaryOp :
{
public:
typedef typename internal::remove_all<BinaryOp>::type Functor;
typedef typename internal::remove_all<LhsType>::type Lhs;
typedef typename internal::remove_all<RhsType>::type Rhs;

View File

@@ -105,7 +105,7 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
*/
template<typename Derived>
template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
{
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func);
@@ -150,7 +150,7 @@ DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
*/
template<typename Derived>
template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
{
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func);
@@ -192,7 +192,7 @@ DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
* \sa class CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(Index size, const Scalar& value)
{
return DenseBase<Derived>::NullaryExpr(size, internal::scalar_constant_op<Scalar>(value));
@@ -208,7 +208,7 @@ DenseBase<Derived>::Constant(Index size, const Scalar& value)
* \sa class CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(const Scalar& value)
{
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
@@ -220,7 +220,7 @@ DenseBase<Derived>::Constant(const Scalar& value)
* \sa LinSpaced(Index,Scalar,Scalar), setLinSpaced(Index,const Scalar&,const Scalar&)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
@@ -232,7 +232,7 @@ DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const
* \sa LinSpaced(Scalar,Scalar)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
@@ -264,7 +264,7 @@ DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& hig
* \sa setLinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
@@ -276,7 +276,7 @@ DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
* Special version for fixed size types which does not require the size parameter.
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
@@ -286,7 +286,7 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
template<typename Derived>
bool DenseBase<Derived>::isApproxToConstant
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApproxToConstant
(const Scalar& val, const RealScalar& prec) const
{
typename internal::nested_eval<Derived,1>::type self(derived());
@@ -301,7 +301,7 @@ bool DenseBase<Derived>::isApproxToConstant
*
* \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template<typename Derived>
bool DenseBase<Derived>::isConstant
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isConstant
(const Scalar& val, const RealScalar& prec) const
{
return isApproxToConstant(val, prec);
@@ -312,7 +312,7 @@ bool DenseBase<Derived>::isConstant
* \sa setConstant(), Constant(), class CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
{
setConstant(val);
}
@@ -322,7 +322,7 @@ EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
* \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
{
return derived() = Constant(rows(), cols(), val);
}
@@ -337,7 +337,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
{
resize(size);
@@ -356,7 +356,7 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
{
resize(rows, cols);
@@ -380,7 +380,7 @@ PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
* \sa LinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,PacketScalar>(low,high,newSize));
@@ -400,7 +400,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, con
* \sa LinSpaced(Index,const Scalar&,const Scalar&), setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return setLinSpaced(size(), low, high);
@@ -423,7 +423,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low,
* \sa Zero(), Zero(Index)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Zero(Index rows, Index cols)
{
return Constant(rows, cols, Scalar(0));
@@ -446,7 +446,7 @@ DenseBase<Derived>::Zero(Index rows, Index cols)
* \sa Zero(), Zero(Index,Index)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Zero(Index size)
{
return Constant(size, Scalar(0));
@@ -463,7 +463,7 @@ DenseBase<Derived>::Zero(Index size)
* \sa Zero(Index), Zero(Index,Index)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Zero()
{
return Constant(Scalar(0));
@@ -478,7 +478,7 @@ DenseBase<Derived>::Zero()
* \sa class CwiseNullaryOp, Zero()
*/
template<typename Derived>
bool DenseBase<Derived>::isZero(const RealScalar& prec) const
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isZero(const RealScalar& prec) const
{
typename internal::nested_eval<Derived,1>::type self(derived());
for(Index j = 0; j < cols(); ++j)
@@ -496,7 +496,7 @@ bool DenseBase<Derived>::isZero(const RealScalar& prec) const
* \sa class CwiseNullaryOp, Zero()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
{
return setConstant(Scalar(0));
}
@@ -511,7 +511,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
* \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setZero(Index newSize)
{
resize(newSize);
@@ -529,7 +529,7 @@ PlainObjectBase<Derived>::setZero(Index newSize)
* \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setZero(Index rows, Index cols)
{
resize(rows, cols);
@@ -553,7 +553,7 @@ PlainObjectBase<Derived>::setZero(Index rows, Index cols)
* \sa Ones(), Ones(Index), isOnes(), class Ones
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Ones(Index rows, Index cols)
{
return Constant(rows, cols, Scalar(1));
@@ -576,7 +576,7 @@ DenseBase<Derived>::Ones(Index rows, Index cols)
* \sa Ones(), Ones(Index,Index), isOnes(), class Ones
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Ones(Index newSize)
{
return Constant(newSize, Scalar(1));
@@ -593,7 +593,7 @@ DenseBase<Derived>::Ones(Index newSize)
* \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Ones()
{
return Constant(Scalar(1));
@@ -608,7 +608,7 @@ DenseBase<Derived>::Ones()
* \sa class CwiseNullaryOp, Ones()
*/
template<typename Derived>
bool DenseBase<Derived>::isOnes
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isOnes
(const RealScalar& prec) const
{
return isApproxToConstant(Scalar(1), prec);
@@ -622,7 +622,7 @@ bool DenseBase<Derived>::isOnes
* \sa class CwiseNullaryOp, Ones()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
{
return setConstant(Scalar(1));
}
@@ -637,7 +637,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
* \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setOnes(Index newSize)
{
resize(newSize);
@@ -655,7 +655,7 @@ PlainObjectBase<Derived>::setOnes(Index newSize)
* \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
{
resize(rows, cols);
@@ -679,7 +679,7 @@ PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
* \sa Identity(), setIdentity(), isIdentity()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
MatrixBase<Derived>::Identity(Index rows, Index cols)
{
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
@@ -696,7 +696,7 @@ MatrixBase<Derived>::Identity(Index rows, Index cols)
* \sa Identity(Index,Index), setIdentity(), isIdentity()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
MatrixBase<Derived>::Identity()
{
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
@@ -771,7 +771,7 @@ struct setIdentity_impl<Derived, true>
* \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
{
return internal::setIdentity_impl<Derived>::run(derived());
}
@@ -787,7 +787,7 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
* \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
{
derived().resize(rows, cols);
return setIdentity();
@@ -800,7 +800,7 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index
* \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
@@ -815,7 +815,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
* \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return BasisReturnType(SquareMatrixType::Identity(),i);
@@ -828,7 +828,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
{ return Derived::Unit(0); }
/** \returns an expression of the Y axis unit vector (0,1{,0}^*)
@@ -838,7 +838,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
{ return Derived::Unit(1); }
/** \returns an expression of the Z axis unit vector (0,0,1{,0}^*)
@@ -848,7 +848,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
{ return Derived::Unit(2); }
/** \returns an expression of the W axis unit vector (0,0,0,1)
@@ -858,7 +858,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
{ return Derived::Unit(3); }
} // end namespace Eigen

View File

@@ -296,7 +296,7 @@ template<typename Derived> class DenseBase
EIGEN_DEVICE_FUNC
Derived& operator=(const ReturnByValue<OtherDerived>& func);
/** \ínternal
/** \internal
* Copies \a other into *this without evaluating other. \returns a reference to *this.
* \deprecated */
template<typename OtherDerived>
@@ -463,7 +463,17 @@ template<typename Derived> class DenseBase
EIGEN_DEVICE_FUNC
void visit(Visitor& func) const;
inline const WithFormat<Derived> format(const IOFormat& fmt) const;
/** \returns a WithFormat proxy object allowing to print a matrix the with given
* format \a fmt.
*
* See class IOFormat for some examples.
*
* \sa class IOFormat, class WithFormat
*/
inline const WithFormat<Derived> format(const IOFormat& fmt) const
{
return WithFormat<Derived>(derived(), fmt);
}
/** \returns the unique coefficient of a 1x1 expression */
EIGEN_DEVICE_FUNC
@@ -474,9 +484,9 @@ template<typename Derived> class DenseBase
return derived().coeff(0,0);
}
bool all() const;
bool any() const;
Index count() const;
EIGEN_DEVICE_FUNC bool all() const;
EIGEN_DEVICE_FUNC bool any() const;
EIGEN_DEVICE_FUNC Index count() const;
typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
typedef const VectorwiseOp<const Derived, Horizontal> ConstRowwiseReturnType;

View File

@@ -13,9 +13,9 @@
#define EIGEN_MATRIXSTORAGE_H
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) X; EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
#else
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
#endif
namespace Eigen {
@@ -184,12 +184,16 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
{
internal::plain_array<T,Size,_Options> m_data;
public:
EIGEN_DEVICE_FUNC DenseStorage() {}
EIGEN_DEVICE_FUNC DenseStorage() {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
}
EIGEN_DEVICE_FUNC
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()) {}
EIGEN_DEVICE_FUNC
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
}
EIGEN_DEVICE_FUNC
DenseStorage& operator=(const DenseStorage& other)
{
@@ -197,7 +201,7 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
return *this;
}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
EIGEN_UNUSED_VARIABLE(size);
EIGEN_UNUSED_VARIABLE(rows);
@@ -343,7 +347,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0);
}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
@@ -351,6 +355,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
, m_rows(other.m_rows)
, m_cols(other.m_cols)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*m_cols)
internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
@@ -403,7 +408,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
else
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_rows = rows;
m_cols = cols;
@@ -422,7 +427,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0);
EIGEN_UNUSED_VARIABLE(rows);
}
@@ -430,6 +435,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
, m_cols(other.m_cols)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows)
internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
@@ -477,7 +483,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
else
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_cols = cols;
}
@@ -495,7 +501,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols);
EIGEN_UNUSED_VARIABLE(cols);
}
@@ -503,6 +509,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
, m_rows(other.m_rows)
{
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols)
internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
@@ -550,7 +557,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
else
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_rows = rows;
}

View File

@@ -21,7 +21,7 @@ namespace Eigen {
* \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
* \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
* A positive value means a superdiagonal, a negative value means a subdiagonal.
* You can also use Dynamic so the index can be set at runtime.
* You can also use DynamicIndex so the index can be set at runtime.
*
* The matrix is not required to be square.
*
@@ -70,7 +70,10 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
EIGEN_DEVICE_FUNC
explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index)
{
eigen_assert( a_index <= m_matrix.cols() && -a_index <= m_matrix.rows() );
}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)

View File

@@ -31,7 +31,8 @@ struct dot_nocheck
typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
typedef typename conj_prod::result_type ResScalar;
EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
EIGEN_STRONG_INLINE
static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{
return a.template binaryExpr<conj_prod>(b).sum();
}
@@ -43,7 +44,8 @@ struct dot_nocheck<T, U, true>
typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
typedef typename conj_prod::result_type ResScalar;
EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
EIGEN_STRONG_INLINE
static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{
return a.transpose().template binaryExpr<conj_prod>(b).sum();
}
@@ -51,7 +53,8 @@ struct dot_nocheck<T, U, true>
} // end namespace internal
/** \returns the dot product of *this with other.
/** \fn MatrixBase::dot
* \returns the dot product of *this with other.
*
* \only_for_vectors
*
@@ -64,15 +67,18 @@ struct dot_nocheck<T, U, true>
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE
typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
#if !(defined(EIGEN_NO_STATIC_ASSERT) && defined(EIGEN_NO_DEBUG))
typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
#endif
eigen_assert(size() == other.size());
return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
@@ -99,7 +105,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
* \sa lpNorm(), dot(), squaredNorm()
*/
template<typename Derived>
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
{
return numext::sqrt(squaredNorm());
}
@@ -114,7 +120,7 @@ inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real Matr
* \sa norm(), normalize()
*/
template<typename Derived>
inline const typename MatrixBase<Derived>::PlainObject
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::normalized() const
{
typedef typename internal::nested_eval<Derived,2>::type _Nested;
@@ -136,7 +142,7 @@ MatrixBase<Derived>::normalized() const
* \sa norm(), normalized()
*/
template<typename Derived>
inline void MatrixBase<Derived>::normalize()
EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
{
RealScalar z = squaredNorm();
// NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
@@ -157,7 +163,7 @@ inline void MatrixBase<Derived>::normalize()
* \sa stableNorm(), stableNormalize(), normalized()
*/
template<typename Derived>
inline const typename MatrixBase<Derived>::PlainObject
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::stableNormalized() const
{
typedef typename internal::nested_eval<Derived,3>::type _Nested;
@@ -182,7 +188,7 @@ MatrixBase<Derived>::stableNormalized() const
* \sa stableNorm(), stableNormalized(), normalize()
*/
template<typename Derived>
inline void MatrixBase<Derived>::stableNormalize()
EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize()
{
RealScalar w = cwiseAbs().maxCoeff();
RealScalar z = (derived()/w).squaredNorm();

View File

@@ -14,6 +14,7 @@
namespace Eigen {
/** \class EigenBase
* \ingroup Core_Module
*
* Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
*
@@ -128,6 +129,7 @@ template<typename Derived> struct EigenBase
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived());
@@ -136,6 +138,7 @@ Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -144,6 +147,7 @@ Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());

View File

@@ -24,11 +24,17 @@ template<int Rows, int Cols, int Depth> struct product_type_selector;
template<int Size, int MaxSize> struct product_size_category
{
enum { is_large = MaxSize == Dynamic ||
Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
value = is_large ? Large
: Size == 1 ? 1
: Small
enum {
#ifndef EIGEN_CUDA_ARCH
is_large = MaxSize == Dynamic ||
Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD ||
(Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD),
#else
is_large = 0,
#endif
value = is_large ? Large
: Size == 1 ? 1
: Small
};
};
@@ -223,50 +229,65 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
// on, the other hand it is good for the cache to pack the vector anyways...
EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime==1),
ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
MightCannotUseDest = (ActualDest::InnerStrideAtCompileTime!=1) || ComplexByReal
MightCannotUseDest = (!EvalToDestAtCompileTime) || ComplexByReal
};
gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
evalToDest ? dest.data() : static_dest.data());
if(!evalToDest)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
Index size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
if(!alphaIsCompatible)
{
MappedDest(actualDestPtr, dest.size()).setZero();
compatibleAlpha = RhsScalar(1);
}
else
MappedDest(actualDestPtr, dest.size()) = dest;
}
typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
general_matrix_vector_product
<Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
actualDestPtr, 1,
compatibleAlpha);
RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
if (!evalToDest)
if(!MightCannotUseDest)
{
if(!alphaIsCompatible)
dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
else
dest = MappedDest(actualDestPtr, dest.size());
// shortcut if we are sure to be able to use dest directly,
// this ease the compiler to generate cleaner and more optimzized code for most common cases
general_matrix_vector_product
<Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
dest.data(), 1,
compatibleAlpha);
}
else
{
gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
evalToDest ? dest.data() : static_dest.data());
if(!evalToDest)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
Index size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
if(!alphaIsCompatible)
{
MappedDest(actualDestPtr, dest.size()).setZero();
compatibleAlpha = RhsScalar(1);
}
else
MappedDest(actualDestPtr, dest.size()) = dest;
}
general_matrix_vector_product
<Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
actualDestPtr, 1,
compatibleAlpha);
if (!evalToDest)
{
if(!alphaIsCompatible)
dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size());
else
dest = MappedDest(actualDestPtr, dest.size());
}
}
}
};
@@ -329,6 +350,7 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,false>
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
{
EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
// TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, otherwise use a temp
typename nested_eval<Rhs,1>::type actual_rhs(rhs);
const Index size = rhs.rows();
@@ -342,6 +364,7 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,false>
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
{
EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
typename nested_eval<Rhs,Lhs::RowsAtCompileTime>::type actual_rhs(rhs);
const Index rows = dest.rows();
for(Index i=0; i<rows; ++i)
@@ -361,8 +384,6 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,false>
*
* \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
*/
#ifndef __CUDACC__
template<typename Derived>
template<typename OtherDerived>
inline const Product<Derived, OtherDerived>
@@ -394,8 +415,6 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
return Product<Derived, OtherDerived>(derived(), other.derived());
}
#endif // __CUDACC__
/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
*
* The returned product will behave like any other expressions: the coefficients of the product will be

View File

@@ -230,7 +230,7 @@ pload1(const typename unpacket_traits<Packet>::type *a) { return pset1<Packet>(
* duplicated to form: {from[0],from[0],from[1],from[1],from[2],from[2],from[3],from[3]}
* Currently, this function is only used for scalar * complex products.
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet with elements of \a *from quadrupled.
@@ -278,7 +278,7 @@ inline void pbroadcast2(const typename unpacket_traits<Packet>::type *a,
}
/** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
template<typename Packet> inline Packet
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
plset(const typename unpacket_traits<Packet>::type& a) { return a; }
/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
@@ -482,7 +482,7 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& fro
* by the current computation.
*/
template<typename Packet, int LoadMode>
inline Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
{
return ploadt<Packet, LoadMode>(from);
}

View File

@@ -105,24 +105,10 @@ class WithFormat
}
protected:
const typename ExpressionType::Nested m_matrix;
typename ExpressionType::Nested m_matrix;
IOFormat m_format;
};
/** \returns a WithFormat proxy object allowing to print a matrix the with given
* format \a fmt.
*
* See class IOFormat for some examples.
*
* \sa class IOFormat, class WithFormat
*/
template<typename Derived>
inline const WithFormat<Derived>
DenseBase<Derived>::format(const IOFormat& fmt) const
{
return WithFormat<Derived>(derived(), fmt);
}
namespace internal {
// NOTE: This helper is kept for backward compatibility with previous code specializing

View File

@@ -45,6 +45,7 @@ class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::S
public:
typedef typename XprType::StorageIndex StorageIndex;
typedef typename XprType::PlainObject PlainObject;
typedef typename XprType::Scalar Scalar;
typedef typename internal::ref_selector<XprType>::type XprTypeNested;
typedef typename internal::remove_all<XprTypeNested>::type XprTypeNestedCleaned;
typedef typename internal::ref_selector<Inverse>::type Nested;

View File

@@ -20,11 +20,17 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
{
typedef traits<PlainObjectType> TraitsBase;
enum {
PlainObjectTypeInnerSize = ((traits<PlainObjectType>::Flags&RowMajorBit)==RowMajorBit)
? PlainObjectType::ColsAtCompileTime
: PlainObjectType::RowsAtCompileTime,
InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
? int(PlainObjectType::InnerStrideAtCompileTime)
: int(StrideType::InnerStrideAtCompileTime),
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
? int(PlainObjectType::OuterStrideAtCompileTime)
? (InnerStrideAtCompileTime==Dynamic || PlainObjectTypeInnerSize==Dynamic
? Dynamic
: int(InnerStrideAtCompileTime) * int(PlainObjectTypeInnerSize))
: int(StrideType::OuterStrideAtCompileTime),
Alignment = int(MapOptions)&int(AlignedMask),
Flags0 = TraitsBase::Flags & (~NestByRefBit),
@@ -107,10 +113,11 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
: IsVectorAtCompileTime ? this->size()
: int(Flags)&RowMajorBit ? this->cols()
: this->rows();
return int(StrideType::OuterStrideAtCompileTime) != 0 ? m_stride.outer()
: int(internal::traits<Map>::OuterStrideAtCompileTime) != Dynamic ? Index(internal::traits<Map>::OuterStrideAtCompileTime)
: IsVectorAtCompileTime ? (this->size() * innerStride())
: (int(Flags)&RowMajorBit) ? (this->cols() * innerStride())
: (this->rows() * innerStride());
}
/** Constructor in the fixed-size case.

View File

@@ -43,6 +43,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
enum {
RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
InnerStrideAtCompileTime = internal::traits<Derived>::InnerStrideAtCompileTime,
SizeAtCompileTime = Base::SizeAtCompileTime
};
@@ -187,8 +188,11 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
void checkSanity(typename internal::enable_if<(internal::traits<T>::Alignment>0),void*>::type = 0) const
{
#if EIGEN_MAX_ALIGN_BYTES>0
// innerStride() is not set yet when this function is called, so we optimistically assume the lowest plausible value:
const Index minInnerStride = InnerStrideAtCompileTime == Dynamic ? 1 : Index(InnerStrideAtCompileTime);
EIGEN_ONLY_USED_FOR_DEBUG(minInnerStride);
eigen_assert(( ((internal::UIntPtr(m_data) % internal::traits<Derived>::Alignment) == 0)
|| (cols() * rows() * innerStride() * sizeof(Scalar)) < internal::traits<Derived>::Alignment ) && "data is not aligned");
|| (cols() * rows() * minInnerStride * sizeof(Scalar)) < internal::traits<Derived>::Alignment ) && "data is not aligned");
#endif
}

View File

@@ -348,31 +348,7 @@ struct norm1_retval
* Implementation of hypot *
****************************************************************************/
template<typename Scalar>
struct hypot_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
static inline RealScalar run(const Scalar& x, const Scalar& y)
{
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD_MATH(sqrt);
RealScalar _x = abs(x);
RealScalar _y = abs(y);
Scalar p, qp;
if(_x>_y)
{
p = _x;
qp = _y / p;
}
else
{
p = _y;
qp = _x / p;
}
if(p==RealScalar(0)) return RealScalar(0);
return p * sqrt(RealScalar(1) + qp*qp);
}
};
template<typename Scalar> struct hypot_impl;
template<typename Scalar>
struct hypot_retval
@@ -495,7 +471,7 @@ namespace std_fallback {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_USING_STD_MATH(log);
Scalar x1p = RealScalar(1) + x;
return ( x1p == Scalar(1) ) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) );
return numext::equal_strict(x1p, Scalar(1)) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) );
}
}
@@ -640,21 +616,28 @@ template<typename Scalar>
struct random_default_impl<Scalar, false, true>
{
static inline Scalar run(const Scalar& x, const Scalar& y)
{
typedef typename conditional<NumTraits<Scalar>::IsSigned,std::ptrdiff_t,std::size_t>::type ScalarX;
if(y<x)
{
if (y <= x)
return x;
// the following difference might overflow on a 32 bits system,
// but since y>=x the result converted to an unsigned long is still correct.
std::size_t range = ScalarX(y)-ScalarX(x);
std::size_t offset = 0;
// rejection sampling
std::size_t divisor = 1;
std::size_t multiplier = 1;
if(range<RAND_MAX) divisor = (std::size_t(RAND_MAX)+1)/(range+1);
else multiplier = 1 + range/(std::size_t(RAND_MAX)+1);
// ScalarU is the unsigned counterpart of Scalar, possibly Scalar itself.
typedef typename make_unsigned<Scalar>::type ScalarU;
// ScalarX is the widest of ScalarU and unsigned int.
// We'll deal only with ScalarX and unsigned int below thus avoiding signed
// types and arithmetic and signed overflows (which are undefined behavior).
typedef typename conditional<(ScalarU(-1) > unsigned(-1)), ScalarU, unsigned>::type ScalarX;
// The following difference doesn't overflow, provided our integer types are two's
// complement and have the same number of padding bits in signed and unsigned variants.
// This is the case in most modern implementations of C++.
ScalarX range = ScalarX(y) - ScalarX(x);
ScalarX offset = 0;
ScalarX divisor = 1;
ScalarX multiplier = 1;
const unsigned rand_max = RAND_MAX;
if (range <= rand_max) divisor = (rand_max + 1) / (range + 1);
else multiplier = 1 + range / (rand_max + 1);
// Rejection sampling.
do {
offset = (std::size_t(std::rand()) * multiplier) / divisor;
offset = (unsigned(std::rand()) * multiplier) / divisor;
} while (offset > range);
return Scalar(ScalarX(x) + offset);
}
@@ -1030,7 +1013,8 @@ inline int log2(int x)
/** \returns the square root of \a x.
*
* It is essentially equivalent to \code using std::sqrt; return sqrt(x); \endcode,
* It is essentially equivalent to
* \code using std::sqrt; return sqrt(x); \endcode
* but slightly faster for float/double and some compilers (e.g., gcc), thanks to
* specializations when SSE is enabled.
*
@@ -1061,11 +1045,24 @@ double log(const double &x) { return ::log(x); }
template<typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
typename NumTraits<T>::Real abs(const T &x) {
typename internal::enable_if<NumTraits<T>::IsSigned || NumTraits<T>::IsComplex,typename NumTraits<T>::Real>::type
abs(const T &x) {
EIGEN_USING_STD_MATH(abs);
return abs(x);
}
template<typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
typename internal::enable_if<!(NumTraits<T>::IsSigned || NumTraits<T>::IsComplex),typename NumTraits<T>::Real>::type
abs(const T &x) {
return x;
}
#if defined(__SYCL_DEVICE_ONLY__)
EIGEN_ALWAYS_INLINE float abs(float x) { return cl::sycl::fabs(x); }
EIGEN_ALWAYS_INLINE double abs(double x) { return cl::sycl::fabs(x); }
#endif // defined(__SYCL_DEVICE_ONLY__)
#ifdef __CUDACC__
template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
float abs(const float &x) { return ::fabsf(x); }

View File

@@ -71,6 +71,29 @@ T generic_fast_tanh_float(const T& a_x)
return pdiv(p, q);
}
template<typename RealScalar>
EIGEN_STRONG_INLINE
RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y)
{
EIGEN_USING_STD_MATH(sqrt);
RealScalar p, qp;
p = numext::maxi(x,y);
if(p==RealScalar(0)) return RealScalar(0);
qp = numext::mini(y,x) / p;
return p * sqrt(RealScalar(1) + qp*qp);
}
template<typename Scalar>
struct hypot_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
static inline RealScalar run(const Scalar& x, const Scalar& y)
{
EIGEN_USING_STD_MATH(abs);
return positive_real_hypot<RealScalar>(abs(x), abs(y));
}
};
} // end namespace internal
} // end namespace Eigen

View File

@@ -274,8 +274,6 @@ class Matrix
: Base(std::move(other))
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
}
EIGEN_DEVICE_FUNC
Matrix& operator=(Matrix&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)

View File

@@ -160,20 +160,11 @@ template<typename Derived> class MatrixBase
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
Derived& operator-=(const MatrixBase<OtherDerived>& other);
#ifdef __CUDACC__
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
const Product<Derived,OtherDerived,LazyProduct>
operator*(const MatrixBase<OtherDerived> &other) const
{ return this->lazyProduct(other); }
#else
template<typename OtherDerived>
const Product<Derived,OtherDerived>
operator*(const MatrixBase<OtherDerived> &other) const;
#endif
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
const Product<Derived,OtherDerived,LazyProduct>
@@ -294,7 +285,7 @@ template<typename Derived> class MatrixBase
* fuzzy comparison such as isApprox()
* \sa isApprox(), operator!= */
template<typename OtherDerived>
inline bool operator==(const MatrixBase<OtherDerived>& other) const
EIGEN_DEVICE_FUNC inline bool operator==(const MatrixBase<OtherDerived>& other) const
{ return cwiseEqual(other).all(); }
/** \returns true if at least one pair of coefficients of \c *this and \a other are not exactly equal to each other.
@@ -302,7 +293,7 @@ template<typename Derived> class MatrixBase
* fuzzy comparison such as isApprox()
* \sa isApprox(), operator== */
template<typename OtherDerived>
inline bool operator!=(const MatrixBase<OtherDerived>& other) const
EIGEN_DEVICE_FUNC inline bool operator!=(const MatrixBase<OtherDerived>& other) const
{ return cwiseNotEqual(other).any(); }
NoAlias<Derived,Eigen::MatrixBase > noalias();
@@ -453,16 +444,24 @@ template<typename Derived> class MatrixBase
///////// MatrixFunctions module /////////
typedef typename internal::stem_function<Scalar>::type StemFunction;
const MatrixExponentialReturnValue<Derived> exp() const;
#define EIGEN_MATRIX_FUNCTION(ReturnType, Name, Description) \
/** \returns an expression of the matrix Description of \c *this. \brief This function requires the <a href="unsupported/group__MatrixFunctions__Module.html"> unsupported MatrixFunctions module</a>. To compute the coefficient-wise Description use ArrayBase::##Name . */ \
const ReturnType<Derived> Name() const;
#define EIGEN_MATRIX_FUNCTION_1(ReturnType, Name, Description, Argument) \
/** \returns an expression of the matrix Description of \c *this. \brief This function requires the <a href="unsupported/group__MatrixFunctions__Module.html"> unsupported MatrixFunctions module</a>. To compute the coefficient-wise Description use ArrayBase::##Name . */ \
const ReturnType<Derived> Name(Argument) const;
EIGEN_MATRIX_FUNCTION(MatrixExponentialReturnValue, exp, exponential)
/** \brief Helper function for the <a href="unsupported/group__MatrixFunctions__Module.html"> unsupported MatrixFunctions module</a>.*/
const MatrixFunctionReturnValue<Derived> matrixFunction(StemFunction f) const;
const MatrixFunctionReturnValue<Derived> cosh() const;
const MatrixFunctionReturnValue<Derived> sinh() const;
const MatrixFunctionReturnValue<Derived> cos() const;
const MatrixFunctionReturnValue<Derived> sin() const;
const MatrixSquareRootReturnValue<Derived> sqrt() const;
const MatrixLogarithmReturnValue<Derived> log() const;
const MatrixPowerReturnValue<Derived> pow(const RealScalar& p) const;
const MatrixComplexPowerReturnValue<Derived> pow(const std::complex<RealScalar>& p) const;
EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cosh, hyperbolic cosine)
EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sinh, hyperbolic sine)
EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cos, cosine)
EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sin, sine)
EIGEN_MATRIX_FUNCTION(MatrixSquareRootReturnValue, sqrt, square root)
EIGEN_MATRIX_FUNCTION(MatrixLogarithmReturnValue, log, logarithm)
EIGEN_MATRIX_FUNCTION_1(MatrixPowerReturnValue, pow, power to \c p, const RealScalar& p)
EIGEN_MATRIX_FUNCTION_1(MatrixComplexPowerReturnValue, pow, power to \c p, const std::complex<RealScalar>& p)
protected:
EIGEN_DEVICE_FUNC MatrixBase() : Base() {}

View File

@@ -215,6 +215,8 @@ struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
EIGEN_DEVICE_FUNC
static inline RealScalar dummy_precision() { return NumTraits<RealScalar>::dummy_precision(); }
static inline int digits10() { return NumTraits<Scalar>::digits10(); }
};
template<> struct NumTraits<std::string>

View File

@@ -41,7 +41,7 @@ template<> struct check_rows_cols_for_overflow<Dynamic> {
{
// http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
// we assume Index is signed
Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
Index max_index = (std::size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
bool error = (rows == 0 || cols == 0) ? false
: (rows > max_index / cols);
if (error)
@@ -58,6 +58,28 @@ template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct m
} // end namespace internal
#ifdef EIGEN_PARSED_BY_DOXYGEN
namespace doxygen {
// This is a workaround to doxygen not being able to understand the inheritance logic
// when it is hidden by the dense_xpr_base helper struct.
// Moreover, doxygen fails to include members that are not documented in the declaration body of
// MatrixBase if we inherits MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >,
// this is why we simply inherits MatrixBase, though this does not make sense.
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename Derived> struct dense_xpr_base_dispatcher;
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public MatrixBase {};
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public ArrayBase {};
} // namespace doxygen
/** \class PlainObjectBase
* \ingroup Core_Module
* \brief %Dense storage base class for matrices and arrays.
@@ -65,26 +87,10 @@ template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct m
* This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_PLAINOBJECTBASE_PLUGIN.
*
* \tparam Derived is the derived type, e.g., a Matrix or Array
*
* \sa \ref TopicClassHierarchy
*/
#ifdef EIGEN_PARSED_BY_DOXYGEN
namespace doxygen {
// this is a workaround to doxygen not being able to understand the inheritance logic
// when it is hidden by the dense_xpr_base helper struct.
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename Derived> struct dense_xpr_base_dispatcher;
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
} // namespace doxygen
template<typename Derived>
class PlainObjectBase : public doxygen::dense_xpr_base_dispatcher<Derived>
#else
@@ -554,7 +560,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
public:
/** \copydoc DenseBase::operator=(const EigenBase<OtherDerived>&)
/** \brief Copies the generic expression \a other into *this.
* \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
@@ -570,6 +577,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned
* \a data pointers.
*
* Here is an example using strides:
* \include Matrix_Map_stride.cpp
* Output: \verbinclude Matrix_Map_stride.out
*
* \see class Map
*/
//@{
@@ -763,6 +774,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
{
// NOTE MSVC 2008 complains if we directly put bool(NumTraits<T>::IsInteger) as the EIGEN_STATIC_ASSERT argument.
const bool is_integer = NumTraits<T>::IsInteger;
EIGEN_UNUSED_VARIABLE(is_integer);
EIGEN_STATIC_ASSERT(is_integer,
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
resize(size);
@@ -804,6 +816,13 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
this->_set_noalias(other);
}
// Initialize an arbitrary matrix from an object convertible to the Derived type.
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Derived& other){
this->_set_noalias(other);
}
// Initialize an arbitrary matrix from a generic Eigen expression
template<typename T, typename OtherDerived>
EIGEN_DEVICE_FUNC
@@ -826,7 +845,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
this->derived() = r;
}
// For fixed -size arrays:
// For fixed-size Array<Scalar,...>
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Scalar& val0,
@@ -838,6 +857,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
Base::setConstant(val0);
}
// For fixed-size Array<Index,...>
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Index& val0,

View File

@@ -97,8 +97,8 @@ class Product : public ProductImpl<_Lhs,_Rhs,Option,
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions");
}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; }
EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; }
@@ -127,7 +127,7 @@ public:
using Base::derived;
typedef typename Base::Scalar Scalar;
operator const Scalar() const
EIGEN_STRONG_INLINE operator const Scalar() const
{
return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
}
@@ -162,7 +162,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense>
public:
EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index row, Index col) const
{
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
@@ -170,7 +170,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense>
return internal::evaluator<Derived>(derived()).coeff(row,col);
}
EIGEN_DEVICE_FUNC Scalar coeff(Index i) const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index i) const
{
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );

View File

@@ -32,7 +32,7 @@ struct evaluator<Product<Lhs, Rhs, Options> >
typedef Product<Lhs, Rhs, Options> XprType;
typedef product_evaluator<XprType> Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
};
// Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B"
@@ -55,7 +55,7 @@ struct evaluator<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
const Product<Lhs, Rhs, DefaultProduct> > XprType;
typedef evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> > Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr)
: Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs())
{}
};
@@ -68,7 +68,7 @@ struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType;
typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr)
: Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>(
Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()),
xpr.index() ))
@@ -158,10 +158,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::add_assign_op<
static EIGEN_STRONG_INLINE
void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
// FIXME shall we handle nested_eval here?
generic_product_impl<Lhs, Rhs>::addTo(dst, src.lhs(), src.rhs());
}
@@ -176,10 +173,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::sub_assign_op<
static EIGEN_STRONG_INLINE
void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
// FIXME shall we handle nested_eval here?
generic_product_impl<Lhs, Rhs>::subTo(dst, src.lhs(), src.rhs());
}
@@ -213,6 +207,12 @@ struct evaluator_assume_aliasing<CwiseBinaryOp<internal::scalar_sum_op<typename
static const bool value = true;
};
template<typename OtherXpr, typename Lhs, typename Rhs>
struct evaluator_assume_aliasing<CwiseBinaryOp<internal::scalar_difference_op<typename OtherXpr::Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, const OtherXpr,
const Product<Lhs,Rhs,DefaultProduct> >, DenseShape > {
static const bool value = true;
};
template<typename DstXprType, typename OtherXpr, typename ProductType, typename Func1, typename Func2>
struct assignment_from_xpr_op_product
{
@@ -246,19 +246,19 @@ template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct>
{
template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); }
};
@@ -312,25 +312,25 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
};
template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major<Dst>());
}
template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major<Dst>());
}
template<typename Dst>
static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>());
}
template<typename Dst>
static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
static EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major<Dst>());
}
@@ -366,17 +366,21 @@ template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct> >
{
typedef typename nested_eval<Lhs,1>::type LhsNested;
typedef typename nested_eval<Rhs,1>::type RhsNested;
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
typedef typename internal::conditional<int(Side)==OnTheRight,Lhs,Rhs>::type MatrixType;
typedef typename internal::remove_all<typename internal::conditional<int(Side)==OnTheRight,LhsNested,RhsNested>::type>::type MatrixType;
template<typename Dest>
static EIGEN_STRONG_INLINE void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
LhsNested actual_lhs(lhs);
RhsNested actual_rhs(rhs);
internal::gemv_dense_selector<Side,
(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
>::run(lhs, rhs, dst, alpha);
>::run(actual_lhs, actual_rhs, dst, alpha);
}
};
@@ -781,7 +785,11 @@ public:
_Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagFlags)&PacketAccessBit))),
_LinearAccessMask = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0,
Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixFlags)) | (_Vectorizable ? PacketAccessBit : 0),
Alignment = evaluator<MatrixType>::Alignment
Alignment = evaluator<MatrixType>::Alignment,
AsScalarProduct = (DiagonalType::SizeAtCompileTime==1)
|| (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::RowsAtCompileTime==1 && ProductOrder==OnTheLeft)
|| (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime==1 && ProductOrder==OnTheRight)
};
diagonal_product_evaluator_base(const MatrixType &mat, const DiagonalType &diag)
@@ -793,7 +801,10 @@ public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
{
return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx);
if(AsScalarProduct)
return m_diagImpl.coeff(0) * m_matImpl.coeff(idx);
else
return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx);
}
protected:

View File

@@ -407,7 +407,7 @@ protected:
*/
template<typename Derived>
template<typename Func>
typename internal::traits<Derived>::Scalar
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::redux(const Func& func) const
{
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");

View File

@@ -95,6 +95,8 @@ protected:
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(Expression& expr)
{
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(PlainObjectType,Expression);
if(PlainObjectType::RowsAtCompileTime==1)
{
eigen_assert(expr.rows()==1 || expr.cols()==1);

View File

@@ -45,7 +45,7 @@ struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
};
}
// FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ??
template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
: public TriangularBase<SelfAdjointView<_MatrixType, UpLo> >
{
@@ -60,16 +60,20 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
/** \brief The type of coefficients in this matrix */
typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
enum {
Mode = internal::traits<SelfAdjointView>::Mode,
Flags = internal::traits<SelfAdjointView>::Flags
Flags = internal::traits<SelfAdjointView>::Flags,
TransposeMode = ((Mode & Upper) ? Lower : 0) | ((Mode & Lower) ? Upper : 0)
};
typedef typename MatrixType::PlainObject PlainObject;
EIGEN_DEVICE_FUNC
explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
{}
{
EIGEN_STATIC_ASSERT(UpLo==Lower || UpLo==Upper,SELFADJOINTVIEW_ACCEPTS_UPPER_AND_LOWER_MODE_ONLY);
}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_matrix.rows(); }
@@ -187,6 +191,36 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type(tmp2);
}
typedef SelfAdjointView<const MatrixConjugateReturnType,UpLo> ConjugateReturnType;
/** \sa MatrixBase::conjugate() const */
EIGEN_DEVICE_FUNC
inline const ConjugateReturnType conjugate() const
{ return ConjugateReturnType(m_matrix.conjugate()); }
typedef SelfAdjointView<const typename MatrixType::AdjointReturnType,TransposeMode> AdjointReturnType;
/** \sa MatrixBase::adjoint() const */
EIGEN_DEVICE_FUNC
inline const AdjointReturnType adjoint() const
{ return AdjointReturnType(m_matrix.adjoint()); }
typedef SelfAdjointView<typename MatrixType::TransposeReturnType,TransposeMode> TransposeReturnType;
/** \sa MatrixBase::transpose() */
EIGEN_DEVICE_FUNC
inline TransposeReturnType transpose()
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
typename MatrixType::TransposeReturnType tmp(m_matrix);
return TransposeReturnType(tmp);
}
typedef SelfAdjointView<const typename MatrixType::ConstTransposeReturnType,TransposeMode> ConstTransposeReturnType;
/** \sa MatrixBase::transpose() const */
EIGEN_DEVICE_FUNC
inline const ConstTransposeReturnType transpose() const
{
return ConstTransposeReturnType(m_matrix.transpose());
}
/** \returns a const expression of the main diagonal of the matrix \c *this
*
* This method simply returns the diagonal of the nested expression, thus by-passing the SelfAdjointView decorator.
@@ -287,6 +321,7 @@ public:
* Implementation of MatrixBase methods
***************************************************************************/
/** This is the const version of MatrixBase::selfadjointView() */
template<typename Derived>
template<unsigned int UpLo>
typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
@@ -295,6 +330,15 @@ MatrixBase<Derived>::selfadjointView() const
return typename ConstSelfAdjointViewReturnType<UpLo>::Type(derived());
}
/** \returns an expression of a symmetric/self-adjoint view extracted from the upper or lower triangular part of the current matrix
*
* The parameter \a UpLo can be either \c #Upper or \c #Lower
*
* Example: \include MatrixBase_selfadjointView.cpp
* Output: \verbinclude MatrixBase_selfadjointView.out
*
* \sa class SelfAdjointView
*/
template<typename Derived>
template<unsigned int UpLo>
typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type

View File

@@ -15,33 +15,29 @@ namespace Eigen {
// TODO generalize the scalar type of 'other'
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator*=(const Scalar& other)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator*=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::mul_assign_op<Scalar,Scalar>());
return derived();
}
template<typename Derived>
EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator+=(const Scalar& other)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator+=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
return derived();
}
template<typename Derived>
EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator-=(const Scalar& other)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator-=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::sub_assign_op<Scalar,Scalar>());
return derived();
}
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator/=(const Scalar& other)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator/=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
return derived();
}

View File

@@ -34,12 +34,12 @@ template<typename Decomposition, typename RhsType,typename StorageKind> struct s
template<typename Decomposition, typename RhsType>
struct solve_traits<Decomposition,RhsType,Dense>
{
typedef Matrix<typename RhsType::Scalar,
typedef typename make_proper_matrix_type<typename RhsType::Scalar,
Decomposition::ColsAtCompileTime,
RhsType::ColsAtCompileTime,
RhsType::PlainObject::Options,
Decomposition::MaxColsAtCompileTime,
RhsType::MaxColsAtCompileTime> PlainObject;
RhsType::MaxColsAtCompileTime>::type PlainObject;
};
template<typename Decomposition, typename RhsType>

View File

@@ -161,6 +161,7 @@ struct triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,CompleteUnrolling,1> {
* TriangularView methods
***************************************************************************/
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename MatrixType, unsigned int Mode>
template<int Side, typename OtherDerived>
void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
@@ -168,6 +169,9 @@ void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<Ot
OtherDerived& other = _other.const_cast_derived();
eigen_assert( derived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols())) );
eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
// If solving for a 0x0 matrix, nothing to do, simply return.
if (derived().cols() == 0)
return;
enum { copy = (internal::traits<OtherDerived>::Flags & RowMajorBit) && OtherDerived::IsVectorAtCompileTime && OtherDerived::SizeAtCompileTime!=1};
typedef typename internal::conditional<copy,
@@ -188,6 +192,7 @@ TriangularViewImpl<Derived,Mode,Dense>::solve(const MatrixBase<Other>& other) co
{
return internal::triangular_solve_retval<Side,TriangularViewType,Other>(derived(), other.derived());
}
#endif
namespace internal {

View File

@@ -165,12 +165,13 @@ MatrixBase<Derived>::stableNorm() const
typedef typename internal::nested_eval<Derived,2>::type DerivedCopy;
typedef typename internal::remove_all<DerivedCopy>::type DerivedCopyClean;
DerivedCopy copy(derived());
const DerivedCopy copy(derived());
enum {
CanAlign = ( (int(DerivedCopyClean::Flags)&DirectAccessBit)
|| (int(internal::evaluator<DerivedCopyClean>::Alignment)>0) // FIXME Alignment)>0 might not be enough
) && (blockSize*sizeof(Scalar)*2<EIGEN_STACK_ALLOCATION_LIMIT) // ifwe cannot allocate on the stack, then let's not bother about this optimization
) && (blockSize*sizeof(Scalar)*2<EIGEN_STACK_ALLOCATION_LIMIT)
&& (EIGEN_MAX_STATIC_ALIGN_BYTES>0) // if we cannot allocate on the stack, then let's not bother about this optimization
};
typedef typename internal::conditional<CanAlign, Ref<const Matrix<Scalar,Dynamic,1,0,blockSize,1>, internal::evaluator<DerivedCopyClean>::Alignment>,
typename DerivedCopyClean::ConstSegmentReturnType>::type SegmentWrapper;

View File

@@ -384,7 +384,7 @@ class Transpose<TranspositionsBase<TranspositionsDerived> >
const Product<OtherDerived, Transpose, AliasFreeProduct>
operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trt)
{
return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt.derived());
return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt);
}
/** \returns the \a matrix with the inverse transpositions applied to the rows.

View File

@@ -470,6 +470,8 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
* \a Side==OnTheLeft (the default), or the right-inverse-multiply \a other * inverse(\c *this) if
* \a Side==OnTheRight.
*
* Note that the template parameter \c Side can be ommitted, in which case \c Side==OnTheLeft
*
* The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the
* diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
* is an upper (resp. lower) triangular matrix.
@@ -495,6 +497,8 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
* \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
* This function will const_cast it, so constness isn't honored here.
*
* Note that the template parameter \c Side can be ommitted, in which case \c Side==OnTheLeft
*
* See TriangularView:solve() for the details.
*/
template<int Side, typename OtherDerived>
@@ -539,13 +543,14 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
template<typename ProductType>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TriangularViewType& _assignProduct(const ProductType& prod, const Scalar& alpha);
EIGEN_STRONG_INLINE TriangularViewType& _assignProduct(const ProductType& prod, const Scalar& alpha, bool beta);
};
/***************************************************************************
* Implementation of triangular evaluation/assignment
***************************************************************************/
#ifndef EIGEN_PARSED_BY_DOXYGEN
// FIXME should we keep that possibility
template<typename MatrixType, unsigned int Mode>
template<typename OtherDerived>
@@ -583,6 +588,7 @@ void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const TriangularBas
eigen_assert(Mode == int(OtherDerived::Mode));
internal::call_assignment_no_alias(derived(), other.derived());
}
#endif
/***************************************************************************
* Implementation of TriangularBase methods
@@ -944,8 +950,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::assign_
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
dst.setZero();
dst._assignProduct(src, 1);
dst._assignProduct(src, 1, 0);
}
};
@@ -956,7 +961,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::add_ass
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,typename SrcXprType::Scalar> &)
{
dst._assignProduct(src, 1);
dst._assignProduct(src, 1, 1);
}
};
@@ -967,7 +972,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::sub_ass
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,typename SrcXprType::Scalar> &)
{
dst._assignProduct(src, -1);
dst._assignProduct(src, -1, 1);
}
};

View File

@@ -194,7 +194,8 @@ struct functor_traits<max_coeff_visitor<Scalar> > {
} // end namespace internal
/** \returns the minimum of all coefficients of *this and puts in *row and *col its location.
/** \fn DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
* \returns the minimum of all coefficients of *this and puts in *row and *col its location.
* \warning the result is undefined if \c *this contains NaN.
*
* \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
@@ -230,7 +231,8 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
return minVisitor.res;
}
/** \returns the maximum of all coefficients of *this and puts in *row and *col its location.
/** \fn DenseBase<Derived>::maxCoeff(IndexType* rowId, IndexType* colId) const
* \returns the maximum of all coefficients of *this and puts in *row and *col its location.
* \warning the result is undefined if \c *this contains NaN.
*
* \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()

View File

@@ -204,23 +204,7 @@ template<> struct conj_helper<Packet4cf, Packet4cf, true,true>
}
};
template<> struct conj_helper<Packet8f, Packet4cf, false,false>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet8f& x, const Packet4cf& y, const Packet4cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet8f& x, const Packet4cf& y) const
{ return Packet4cf(Eigen::internal::pmul(x, y.v)); }
};
template<> struct conj_helper<Packet4cf, Packet8f, false,false>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet8f& y, const Packet4cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& x, const Packet8f& y) const
{ return Packet4cf(Eigen::internal::pmul(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet4cf,Packet8f)
template<> EIGEN_STRONG_INLINE Packet4cf pdiv<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
{
@@ -400,23 +384,7 @@ template<> struct conj_helper<Packet2cd, Packet2cd, true,true>
}
};
template<> struct conj_helper<Packet4d, Packet2cd, false,false>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet4d& x, const Packet2cd& y, const Packet2cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet4d& x, const Packet2cd& y) const
{ return Packet2cd(Eigen::internal::pmul(x, y.v)); }
};
template<> struct conj_helper<Packet2cd, Packet4d, false,false>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet4d& y, const Packet2cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& x, const Packet4d& y) const
{ return Packet2cd(Eigen::internal::pmul(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cd,Packet4d)
template<> EIGEN_STRONG_INLINE Packet2cd pdiv<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
{

View File

@@ -159,11 +159,12 @@ template<> EIGEN_STRONG_INLINE Packet8i pdiv<Packet8i>(const Packet8i& /*a*/, co
#ifdef __FMA__
template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
#if ( EIGEN_COMP_GNUC_STRICT || (EIGEN_COMP_CLANG && (EIGEN_COMP_CLANG<308)) )
// clang stupidly generates a vfmadd213ps instruction plus some vmovaps on registers,
// and gcc stupidly generates a vfmadd132ps instruction,
// so let's enforce it to generate a vfmadd231ps instruction since the most common use case is to accumulate
// the result of the product.
#if ( (EIGEN_COMP_GNUC_STRICT && EIGEN_COMP_GNUC<80) || (EIGEN_COMP_CLANG) )
// Clang stupidly generates a vfmadd213ps instruction plus some vmovaps on registers,
// and even register spilling with clang>=6.0 (bug 1637).
// Gcc stupidly generates a vfmadd132ps instruction.
// So let's enforce it to generate a vfmadd231ps instruction since the most common use
// case is to accumulate the result of the product.
Packet8f res = c;
__asm__("vfmadd231ps %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
return res;
@@ -172,7 +173,7 @@ template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f&
#endif
}
template<> EIGEN_STRONG_INLINE Packet4d pmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
#if ( EIGEN_COMP_GNUC_STRICT || (EIGEN_COMP_CLANG && (EIGEN_COMP_CLANG<308)) )
#if ( (EIGEN_COMP_GNUC_STRICT && EIGEN_COMP_GNUC<80) || (EIGEN_COMP_CLANG) )
// see above
Packet4d res = c;
__asm__("vfmadd231pd %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
@@ -308,9 +309,9 @@ template<> EIGEN_STRONG_INLINE void pstore1<Packet8i>(int* to, const int& a)
}
#ifndef EIGEN_VECTORIZE_AVX512
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
#endif
template<> EIGEN_STRONG_INLINE float pfirst<Packet8f>(const Packet8f& a) {
@@ -333,9 +334,12 @@ template<> EIGEN_STRONG_INLINE Packet4d preverse(const Packet4d& a)
{
__m256d tmp = _mm256_shuffle_pd(a,a,5);
return _mm256_permute2f128_pd(tmp, tmp, 1);
#if 0
// This version is unlikely to be faster as _mm256_shuffle_ps and _mm256_permute_pd
// exhibit the same latency/throughput, but it is here for future reference/benchmarking...
__m256d swap_halves = _mm256_permute2f128_pd(a,a,1);
return _mm256_permute_pd(swap_halves,5);
#endif
}
// pabs should be ok
@@ -395,14 +399,11 @@ template<> EIGEN_STRONG_INLINE Packet4d preduxp<Packet4d>(const Packet4d* vecs)
template<> EIGEN_STRONG_INLINE float predux<Packet8f>(const Packet8f& a)
{
Packet8f tmp0 = _mm256_hadd_ps(a,_mm256_permute2f128_ps(a,a,1));
tmp0 = _mm256_hadd_ps(tmp0,tmp0);
return pfirst(_mm256_hadd_ps(tmp0, tmp0));
return predux(Packet4f(_mm_add_ps(_mm256_castps256_ps128(a),_mm256_extractf128_ps(a,1))));
}
template<> EIGEN_STRONG_INLINE double predux<Packet4d>(const Packet4d& a)
{
Packet4d tmp0 = _mm256_hadd_pd(a,_mm256_permute2f128_pd(a,a,1));
return pfirst(_mm256_hadd_pd(tmp0,tmp0));
return predux(Packet2d(_mm_add_pd(_mm256_castpd256_pd128(a),_mm256_extractf128_pd(a,1))));
}
template<> EIGEN_STRONG_INLINE Packet4f predux_downto4<Packet8f>(const Packet8f& a)

View File

@@ -88,9 +88,9 @@ plog<Packet16f>(const Packet16f& _x) {
// x = x + x - 1.0;
// } else { x = x - 1.0; }
__mmask16 mask = _mm512_cmp_ps_mask(x, p16f_cephes_SQRTHF, _CMP_LT_OQ);
Packet16f tmp = _mm512_mask_blend_ps(mask, x, _mm512_setzero_ps());
Packet16f tmp = _mm512_mask_blend_ps(mask, _mm512_setzero_ps(), x);
x = psub(x, p16f_1);
e = psub(e, _mm512_mask_blend_ps(mask, p16f_1, _mm512_setzero_ps()));
e = psub(e, _mm512_mask_blend_ps(mask, _mm512_setzero_ps(), p16f_1));
x = padd(x, tmp);
Packet16f x2 = pmul(x, x);
@@ -119,8 +119,9 @@ plog<Packet16f>(const Packet16f& _x) {
x = padd(x, y2);
// Filter out invalid inputs, i.e. negative arg will be NAN, 0 will be -INF.
return _mm512_mask_blend_ps(iszero_mask, p16f_minus_inf,
_mm512_mask_blend_ps(invalid_mask, p16f_nan, x));
return _mm512_mask_blend_ps(iszero_mask,
_mm512_mask_blend_ps(invalid_mask, x, p16f_nan),
p16f_minus_inf);
}
#endif
@@ -266,8 +267,7 @@ psqrt<Packet16f>(const Packet16f& _x) {
// select only the inverse sqrt of positive normal inputs (denormals are
// flushed to zero and cause infs as well).
__mmask16 non_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_GE_OQ);
Packet16f x = _mm512_mask_blend_ps(non_zero_mask, _mm512_rsqrt14_ps(_x),
_mm512_setzero_ps());
Packet16f x = _mm512_mask_blend_ps(non_zero_mask, _mm512_setzero_ps(), _mm512_rsqrt14_ps(_x));
// Do a single step of Newton's iteration.
x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five));
@@ -289,8 +289,7 @@ psqrt<Packet8d>(const Packet8d& _x) {
// select only the inverse sqrt of positive normal inputs (denormals are
// flushed to zero and cause infs as well).
__mmask8 non_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_GE_OQ);
Packet8d x = _mm512_mask_blend_pd(non_zero_mask, _mm512_rsqrt14_pd(_x),
_mm512_setzero_pd());
Packet8d x = _mm512_mask_blend_pd(non_zero_mask, _mm512_setzero_pd(), _mm512_rsqrt14_pd(_x));
// Do a first step of Newton's iteration.
x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
@@ -333,20 +332,18 @@ prsqrt<Packet16f>(const Packet16f& _x) {
// select only the inverse sqrt of positive normal inputs (denormals are
// flushed to zero and cause infs as well).
__mmask16 le_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_LT_OQ);
Packet16f x = _mm512_mask_blend_ps(le_zero_mask, _mm512_setzero_ps(),
_mm512_rsqrt14_ps(_x));
Packet16f x = _mm512_mask_blend_ps(le_zero_mask, _mm512_rsqrt14_ps(_x), _mm512_setzero_ps());
// Fill in NaNs and Infs for the negative/zero entries.
__mmask16 neg_mask = _mm512_cmp_ps_mask(_x, _mm512_setzero_ps(), _CMP_LT_OQ);
Packet16f infs_and_nans = _mm512_mask_blend_ps(
neg_mask, p16f_nan,
_mm512_mask_blend_ps(le_zero_mask, p16f_inf, _mm512_setzero_ps()));
neg_mask, _mm512_mask_blend_ps(le_zero_mask, _mm512_setzero_ps(), p16f_inf), p16f_nan);
// Do a single step of Newton's iteration.
x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five));
// Insert NaNs and Infs in all the right places.
return _mm512_mask_blend_ps(le_zero_mask, infs_and_nans, x);
return _mm512_mask_blend_ps(le_zero_mask, x, infs_and_nans);
}
template <>
@@ -363,14 +360,12 @@ prsqrt<Packet8d>(const Packet8d& _x) {
// select only the inverse sqrt of positive normal inputs (denormals are
// flushed to zero and cause infs as well).
__mmask8 le_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_LT_OQ);
Packet8d x = _mm512_mask_blend_pd(le_zero_mask, _mm512_setzero_pd(),
_mm512_rsqrt14_pd(_x));
Packet8d x = _mm512_mask_blend_pd(le_zero_mask, _mm512_rsqrt14_pd(_x), _mm512_setzero_pd());
// Fill in NaNs and Infs for the negative/zero entries.
__mmask8 neg_mask = _mm512_cmp_pd_mask(_x, _mm512_setzero_pd(), _CMP_LT_OQ);
Packet8d infs_and_nans = _mm512_mask_blend_pd(
neg_mask, p8d_nan,
_mm512_mask_blend_pd(le_zero_mask, p8d_inf, _mm512_setzero_pd()));
neg_mask, _mm512_mask_blend_pd(le_zero_mask, _mm512_setzero_pd(), p8d_inf), p8d_nan);
// Do a first step of Newton's iteration.
x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
@@ -379,9 +374,9 @@ prsqrt<Packet8d>(const Packet8d& _x) {
x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
// Insert NaNs and Infs in all the right places.
return _mm512_mask_blend_pd(le_zero_mask, infs_and_nans, x);
return _mm512_mask_blend_pd(le_zero_mask, x, infs_and_nans);
}
#else
#elif defined(EIGEN_VECTORIZE_AVX512ER)
template <>
EIGEN_STRONG_INLINE Packet16f prsqrt<Packet16f>(const Packet16f& x) {
return _mm512_rsqrt28_ps(x);

View File

@@ -618,9 +618,9 @@ EIGEN_STRONG_INLINE void pstore1<Packet16i>(int* to, const int& a) {
pstore(to, pa);
}
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template <>
EIGEN_STRONG_INLINE float pfirst<Packet16f>(const Packet16f& a) {
@@ -648,13 +648,13 @@ template<> EIGEN_STRONG_INLINE Packet8d preverse(const Packet8d& a)
template<> EIGEN_STRONG_INLINE Packet16f pabs(const Packet16f& a)
{
// _mm512_abs_ps intrinsic not found, so hack around it
return (__m512)_mm512_and_si512((__m512i)a, _mm512_set1_epi32(0x7fffffff));
return _mm512_castsi512_ps(_mm512_and_si512(_mm512_castps_si512(a), _mm512_set1_epi32(0x7fffffff)));
}
template <>
EIGEN_STRONG_INLINE Packet8d pabs(const Packet8d& a) {
// _mm512_abs_ps intrinsic not found, so hack around it
return (__m512d)_mm512_and_si512((__m512i)a,
_mm512_set1_epi64(0x7fffffffffffffff));
return _mm512_castsi512_pd(_mm512_and_si512(_mm512_castpd_si512(a),
_mm512_set1_epi64(0x7fffffffffffffff)));
}
#ifdef EIGEN_VECTORIZE_AVX512DQ

View File

@@ -15,14 +15,14 @@ namespace Eigen {
namespace internal {
static Packet4ui p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_ZERO_);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
static Packet4ui p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_MZERO);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
#ifdef __VSX__
#if defined(_BIG_ENDIAN)
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2d_ZERO_, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_ZERO_, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2d_MZERO, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_MZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
#else
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_ZERO_, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2d_ZERO_, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_MZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2d_MZERO, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
#endif
#endif
@@ -65,7 +65,7 @@ template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type;
template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>& from)
{
Packet2cf res;
if((ptrdiff_t(&from) % 16) == 0)
if((std::ptrdiff_t(&from) % 16) == 0)
res.v = pload<Packet4f>((const float *)&from);
else
res.v = ploadu<Packet4f>((const float *)&from);
@@ -224,23 +224,7 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true>
}
};
template<> struct conj_helper<Packet4f, Packet2cf, false,false>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const
{ return Packet2cf(internal::pmul<Packet4f>(x, y.v)); }
};
template<> struct conj_helper<Packet2cf, Packet4f, false,false>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const
{ return Packet2cf(internal::pmul<Packet4f>(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
{
@@ -416,23 +400,8 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
return pconj(internal::pmul(a, b));
}
};
template<> struct conj_helper<Packet2d, Packet1cd, false,false>
{
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const
{ return Packet1cd(internal::pmul<Packet2d>(x, y.v)); }
};
template<> struct conj_helper<Packet1cd, Packet2d, false,false>
{
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const
{ return Packet1cd(internal::pmul<Packet2d>(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
{

View File

@@ -84,8 +84,10 @@ static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
#ifdef __POWER8_VECTOR__
static Packet2l p2l_1023 = { 1023, 1023 };
static Packet2ul p2ul_52 = { 52, 52 };
#endif
#endif

View File

@@ -72,7 +72,7 @@ static _EIGEN_DECLARE_CONST_FAST_Packet4i(ZERO, 0); //{ 0, 0, 0, 0,}
static _EIGEN_DECLARE_CONST_FAST_Packet4i(ONE,1); //{ 1, 1, 1, 1}
static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS16,-16); //{ -16, -16, -16, -16}
static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS1,-1); //{ -1, -1, -1, -1}
static Packet4f p4f_ZERO_ = (Packet4f) vec_sl((Packet4ui)p4i_MINUS1, (Packet4ui)p4i_MINUS1); //{ 0x80000000, 0x80000000, 0x80000000, 0x80000000}
static Packet4f p4f_MZERO = (Packet4f) vec_sl((Packet4ui)p4i_MINUS1, (Packet4ui)p4i_MINUS1); //{ 0x80000000, 0x80000000, 0x80000000, 0x80000000}
#ifndef __VSX__
static Packet4f p4f_ONE = vec_ctf(p4i_ONE, 0); //{ 1.0, 1.0, 1.0, 1.0}
#endif
@@ -90,7 +90,7 @@ static Packet16uc p16uc_DUPLICATE32_HI = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7 };
#define _EIGEN_MASK_ALIGNMENT 0xfffffff0
#endif
#define _EIGEN_ALIGNED_PTR(x) ((ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
#define _EIGEN_ALIGNED_PTR(x) ((std::ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
// Handle endianness properly while loading constants
// Define global static constants:
@@ -103,7 +103,7 @@ static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4u
static Packet16uc p16uc_PSET32_WEVEN = vec_sld(p16uc_DUPLICATE32_HI, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
static Packet16uc p16uc_HALF64_0_16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8); //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
#else
static Packet16uc p16uc_FORWARD = p16uc_REVERSE32;
static Packet16uc p16uc_FORWARD = p16uc_REVERSE32;
static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 1), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
static Packet16uc p16uc_PSET32_WEVEN = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
@@ -358,7 +358,7 @@ template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a) { return p4i_
template<> EIGEN_STRONG_INLINE Packet4f pconj(const Packet4f& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet4i pconj(const Packet4i& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_madd(a,b, p4f_ZERO); }
template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_madd(a,b, p4f_MZERO); }
template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b) { return a * b; }
template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
@@ -373,7 +373,7 @@ template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const
t = vec_nmsub(y_0, b, p4f_ONE);
y_1 = vec_madd(y_0, t, y_0);
return vec_madd(a, y_1, p4f_ZERO);
return vec_madd(a, y_1, p4f_MZERO);
#else
return vec_div(a, b);
#endif
@@ -388,10 +388,28 @@ template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, co
template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vec_madd(a,b,c); }
template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return a*b + c; }
template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_min(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b)
{
#ifdef __VSX__
Packet4f ret;
__asm__ ("xvcmpgesp %x0,%x1,%x2\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b));
return ret;
#else
return vec_min(a, b);
#endif
}
template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_min(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_max(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b)
{
#ifdef __VSX__
Packet4f ret;
__asm__ ("xvcmpgtsp %x0,%x2,%x1\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b));
return ret;
#else
return vec_max(a, b);
#endif
}
template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, b); }
@@ -450,15 +468,15 @@ template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
{
Packet4f p;
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet4f>(from);
else p = ploadu<Packet4f>(from);
if((std::ptrdiff_t(from) % 16) == 0) p = pload<Packet4f>(from);
else p = ploadu<Packet4f>(from);
return vec_perm(p, p, p16uc_DUPLICATE32_HI);
}
template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int* from)
{
Packet4i p;
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet4i>(from);
else p = ploadu<Packet4i>(from);
if((std::ptrdiff_t(from) % 16) == 0) p = pload<Packet4i>(from);
else p = ploadu<Packet4i>(from);
return vec_perm(p, p, p16uc_DUPLICATE32_HI);
}
@@ -764,9 +782,9 @@ typedef __vector __bool long Packet2bl;
static Packet2l p2l_ONE = { 1, 1 };
static Packet2l p2l_ZERO = reinterpret_cast<Packet2l>(p4i_ZERO);
static Packet2d p2d_ONE = { 1.0, 1.0 };
static Packet2d p2d_ONE = { 1.0, 1.0 };
static Packet2d p2d_ZERO = reinterpret_cast<Packet2d>(p4f_ZERO);
static Packet2d p2d_ZERO_ = { -0.0, -0.0 };
static Packet2d p2d_MZERO = { -0.0, -0.0 };
#ifdef _BIG_ENDIAN
static Packet2d p2d_COUNTDOWN = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(p2d_ZERO), reinterpret_cast<Packet4f>(p2d_ONE), 8));
@@ -904,15 +922,25 @@ template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return p2d_
template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_madd(a,b,p2d_ZERO); }
template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_madd(a,b,p2d_MZERO); }
template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_div(a,b); }
// for some weird raisons, it has to be overloaded for packet of integers
template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); }
template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b)
{
Packet2d ret;
__asm__ ("xvcmpgedp %x0,%x1,%x2\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b));
return ret;
}
template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b)
{
Packet2d ret;
__asm__ ("xvcmpgtdp %x0,%x2,%x1\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b));
return ret;
}
template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); }
@@ -935,8 +963,8 @@ template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from)
template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double* from)
{
Packet2d p;
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet2d>(from);
else p = ploadu<Packet2d>(from);
if((std::ptrdiff_t(from) % 16) == 0) p = pload<Packet2d>(from);
else p = ploadu<Packet2d>(from);
return vec_splat_dbl<0>(p);
}
@@ -969,7 +997,7 @@ template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
Packet2d v[2], sum;
v[0] = vecs[0] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[0]), reinterpret_cast<Packet4f>(vecs[0]), 8));
v[1] = vecs[1] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[1]), reinterpret_cast<Packet4f>(vecs[1]), 8));
#ifdef _BIG_ENDIAN
sum = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(v[0]), reinterpret_cast<Packet4f>(v[1]), 8));
#else
@@ -1022,7 +1050,7 @@ ptranspose(PacketBlock<Packet2d,2>& kernel) {
template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) {
Packet2l select = { ifPacket.select[0], ifPacket.select[1] };
Packet2bl mask = vec_cmpeq(reinterpret_cast<Packet2d>(select), reinterpret_cast<Packet2d>(p2l_ONE));
Packet2bl mask = reinterpret_cast<Packet2bl>( vec_cmpeq(reinterpret_cast<Packet2d>(select), reinterpret_cast<Packet2d>(p2l_ONE)) );
return vec_sel(elsePacket, thenPacket, mask);
}
#endif // __VSX__

View File

@@ -13,7 +13,7 @@
// Redistribution and use in source and binary forms, with or without
// modification, are permitted.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
@@ -29,7 +29,7 @@
// type Eigen::half (inheriting from CUDA's __half struct) with
// operator overloads such that it behaves basically as an arithmetic
// type. It will be quite slow on CPUs (so it is recommended to stay
// in fp32 for CPUs, except for simple parameter conversions, I/O
// in float32_bits for CPUs, except for simple parameter conversions, I/O
// to disk and the likes), but fast on GPUs.
@@ -50,38 +50,45 @@ struct half;
namespace half_impl {
#if !defined(EIGEN_HAS_CUDA_FP16)
// Make our own __half definition that is similar to CUDA's.
struct __half {
EIGEN_DEVICE_FUNC __half() {}
explicit EIGEN_DEVICE_FUNC __half(unsigned short raw) : x(raw) {}
// Make our own __half_raw definition that is similar to CUDA's.
struct __half_raw {
EIGEN_DEVICE_FUNC __half_raw() : x(0) {}
explicit EIGEN_DEVICE_FUNC __half_raw(unsigned short raw) : x(raw) {}
unsigned short x;
};
#elif defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER < 90000
// In CUDA < 9.0, __half is the equivalent of CUDA 9's __half_raw
typedef __half __half_raw;
#endif
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw raw_uint16_to_half(unsigned short x);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw float_to_half_rtne(float ff);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half_raw h);
struct half_base : public __half {
struct half_base : public __half_raw {
EIGEN_DEVICE_FUNC half_base() {}
EIGEN_DEVICE_FUNC half_base(const half_base& h) : __half(h) {}
EIGEN_DEVICE_FUNC half_base(const __half& h) : __half(h) {}
EIGEN_DEVICE_FUNC half_base(const half_base& h) : __half_raw(h) {}
EIGEN_DEVICE_FUNC half_base(const __half_raw& h) : __half_raw(h) {}
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER >= 90000
EIGEN_DEVICE_FUNC half_base(const __half& h) : __half_raw(*(__half_raw*)&h) {}
#endif
};
} // namespace half_impl
// Class definition.
struct half : public half_impl::half_base {
#if !defined(EIGEN_HAS_CUDA_FP16)
typedef half_impl::__half __half;
#if !defined(EIGEN_HAS_CUDA_FP16) || (defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER < 90000)
typedef half_impl::__half_raw __half_raw;
#endif
EIGEN_DEVICE_FUNC half() {}
EIGEN_DEVICE_FUNC half(const __half& h) : half_impl::half_base(h) {}
EIGEN_DEVICE_FUNC half(const __half_raw& h) : half_impl::half_base(h) {}
EIGEN_DEVICE_FUNC half(const half& h) : half_impl::half_base(h) {}
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER >= 90000
EIGEN_DEVICE_FUNC half(const __half& h) : half_impl::half_base(h) {}
#endif
explicit EIGEN_DEVICE_FUNC half(bool b)
: half_impl::half_base(half_impl::raw_uint16_to_half(b ? 0x3c00 : 0)) {}
@@ -138,71 +145,125 @@ struct half : public half_impl::half_base {
}
};
} // end namespace Eigen
namespace std {
template<>
struct numeric_limits<Eigen::half> {
static const bool is_specialized = true;
static const bool is_signed = true;
static const bool is_integer = false;
static const bool is_exact = false;
static const bool has_infinity = true;
static const bool has_quiet_NaN = true;
static const bool has_signaling_NaN = true;
static const float_denorm_style has_denorm = denorm_present;
static const bool has_denorm_loss = false;
static const std::float_round_style round_style = std::round_to_nearest;
static const bool is_iec559 = false;
static const bool is_bounded = false;
static const bool is_modulo = false;
static const int digits = 11;
static const int digits10 = 3; // according to http://half.sourceforge.net/structstd_1_1numeric__limits_3_01half__float_1_1half_01_4.html
static const int max_digits10 = 5; // according to http://half.sourceforge.net/structstd_1_1numeric__limits_3_01half__float_1_1half_01_4.html
static const int radix = 2;
static const int min_exponent = -13;
static const int min_exponent10 = -4;
static const int max_exponent = 16;
static const int max_exponent10 = 4;
static const bool traps = true;
static const bool tinyness_before = false;
static Eigen::half (min)() { return Eigen::half_impl::raw_uint16_to_half(0x400); }
static Eigen::half lowest() { return Eigen::half_impl::raw_uint16_to_half(0xfbff); }
static Eigen::half (max)() { return Eigen::half_impl::raw_uint16_to_half(0x7bff); }
static Eigen::half epsilon() { return Eigen::half_impl::raw_uint16_to_half(0x0800); }
static Eigen::half round_error() { return Eigen::half(0.5); }
static Eigen::half infinity() { return Eigen::half_impl::raw_uint16_to_half(0x7c00); }
static Eigen::half quiet_NaN() { return Eigen::half_impl::raw_uint16_to_half(0x7e00); }
static Eigen::half signaling_NaN() { return Eigen::half_impl::raw_uint16_to_half(0x7e00); }
static Eigen::half denorm_min() { return Eigen::half_impl::raw_uint16_to_half(0x1); }
};
// If std::numeric_limits<T> is specialized, should also specialize
// std::numeric_limits<const T>, std::numeric_limits<volatile T>, and
// std::numeric_limits<const volatile T>
// https://stackoverflow.com/a/16519653/
template<>
struct numeric_limits<const Eigen::half> : numeric_limits<Eigen::half> {};
template<>
struct numeric_limits<volatile Eigen::half> : numeric_limits<Eigen::half> {};
template<>
struct numeric_limits<const volatile Eigen::half> : numeric_limits<Eigen::half> {};
} // end namespace std
namespace Eigen {
namespace half_impl {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
// Intrinsics for native fp16 support. Note that on current hardware,
// these are no faster than fp32 arithmetic (you need to use the half2
// these are no faster than float32_bits arithmetic (you need to use the half2
// versions to get the ALU speed increased), but you do save the
// conversion steps back and forth.
__device__ half operator + (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half operator + (const half& a, const half& b) {
return __hadd(a, b);
}
__device__ half operator * (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half operator * (const half& a, const half& b) {
return __hmul(a, b);
}
__device__ half operator - (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half operator - (const half& a, const half& b) {
return __hsub(a, b);
}
__device__ half operator / (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half operator / (const half& a, const half& b) {
float num = __half2float(a);
float denom = __half2float(b);
return __float2half(num / denom);
}
__device__ half operator - (const half& a) {
EIGEN_STRONG_INLINE __device__ half operator - (const half& a) {
return __hneg(a);
}
__device__ half& operator += (half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half& operator += (half& a, const half& b) {
a = a + b;
return a;
}
__device__ half& operator *= (half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half& operator *= (half& a, const half& b) {
a = a * b;
return a;
}
__device__ half& operator -= (half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half& operator -= (half& a, const half& b) {
a = a - b;
return a;
}
__device__ half& operator /= (half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ half& operator /= (half& a, const half& b) {
a = a / b;
return a;
}
__device__ bool operator == (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator == (const half& a, const half& b) {
return __heq(a, b);
}
__device__ bool operator != (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator != (const half& a, const half& b) {
return __hne(a, b);
}
__device__ bool operator < (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator < (const half& a, const half& b) {
return __hlt(a, b);
}
__device__ bool operator <= (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator <= (const half& a, const half& b) {
return __hle(a, b);
}
__device__ bool operator > (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator > (const half& a, const half& b) {
return __hgt(a, b);
}
__device__ bool operator >= (const half& a, const half& b) {
EIGEN_STRONG_INLINE __device__ bool operator >= (const half& a, const half& b) {
return __hge(a, b);
}
#else // Emulate support for half floats
// Definitions for CPUs and older CUDA, mostly working through conversion
// to/from fp32.
// to/from float32_bits.
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator + (const half& a, const half& b) {
return half(float(a) + float(b));
@@ -238,10 +299,10 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator /= (half& a, const half& b)
return a;
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator == (const half& a, const half& b) {
return float(a) == float(b);
return numext::equal_strict(float(a),float(b));
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator != (const half& a, const half& b) {
return float(a) != float(b);
return numext::not_equal_strict(float(a), float(b));
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator < (const half& a, const half& b) {
return float(a) < float(b);
@@ -269,34 +330,35 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator / (const half& a, Index b) {
// these in hardware. If we need more performance on older/other CPUs, they are
// also possible to vectorize directly.
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x) {
__half h;
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw raw_uint16_to_half(unsigned short x) {
__half_raw h;
h.x = x;
return h;
}
union FP32 {
union float32_bits {
unsigned int u;
float f;
};
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
return __float2half(ff);
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw float_to_half_rtne(float ff) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 300
__half tmp_ff = __float2half(ff);
return *(__half_raw*)&tmp_ff;
#elif defined(EIGEN_HAS_FP16_C)
__half h;
__half_raw h;
h.x = _cvtss_sh(ff, 0);
return h;
#else
FP32 f; f.f = ff;
float32_bits f; f.f = ff;
const FP32 f32infty = { 255 << 23 };
const FP32 f16max = { (127 + 16) << 23 };
const FP32 denorm_magic = { ((127 - 15) + (23 - 10) + 1) << 23 };
const float32_bits f32infty = { 255 << 23 };
const float32_bits f16max = { (127 + 16) << 23 };
const float32_bits denorm_magic = { ((127 - 15) + (23 - 10) + 1) << 23 };
unsigned int sign_mask = 0x80000000u;
__half o;
__half_raw o;
o.x = static_cast<unsigned short>(0x0u);
unsigned int sign = f.u & sign_mask;
@@ -335,17 +397,17 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff) {
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half_raw h) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 300
return __half2float(h);
#elif defined(EIGEN_HAS_FP16_C)
return _cvtsh_ss(h.x);
#else
const FP32 magic = { 113 << 23 };
const float32_bits magic = { 113 << 23 };
const unsigned int shifted_exp = 0x7c00 << 13; // exponent mask after shift
FP32 o;
float32_bits o;
o.u = (h.x & 0x7fff) << 13; // exponent/mantissa bits
unsigned int exp = shifted_exp & o.u; // just the exponent
@@ -370,7 +432,7 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isinf)(const half& a) {
return (a.x & 0x7fff) == 0x7c00;
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isnan)(const half& a) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
return __hisnan(a);
#else
return (a.x & 0x7fff) > 0x7c00;
@@ -386,11 +448,15 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half abs(const half& a) {
return result;
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half exp(const half& a) {
return half(::expf(float(a)));
#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530
return half(hexp(a));
#else
return half(::expf(float(a)));
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log(const half& a) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return Eigen::half(::hlog(a));
#if defined(EIGEN_HAS_CUDA_FP16) && EIGEN_CUDACC_VER >= 80000 && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
return half(::hlog(a));
#else
return half(::logf(float(a)));
#endif
@@ -402,7 +468,11 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log10(const half& a) {
return half(::log10f(float(a)));
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half sqrt(const half& a) {
return half(::sqrtf(float(a)));
#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530
return half(hsqrt(a));
#else
return half(::sqrtf(float(a)));
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half pow(const half& a, const half& b) {
return half(::powf(float(a), float(b)));
@@ -420,14 +490,22 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half tanh(const half& a) {
return half(::tanhf(float(a)));
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half floor(const half& a) {
#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 300
return half(hfloor(a));
#else
return half(::floorf(float(a)));
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half ceil(const half& a) {
#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 300
return half(hceil(a));
#else
return half(::ceilf(float(a)));
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (min)(const half& a, const half& b) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
return __hlt(b, a) ? b : a;
#else
const float f1 = static_cast<float>(a);
@@ -436,7 +514,7 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (min)(const half& a, const half& b) {
#endif
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (max)(const half& a, const half& b) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
#if defined(EIGEN_HAS_CUDA_FP16) && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
return __hlt(a, b) ? b : a;
#else
const float f1 = static_cast<float>(a);
@@ -477,6 +555,13 @@ template<> struct is_arithmetic<half> { enum { value = true }; };
template<> struct NumTraits<Eigen::half>
: GenericNumTraits<Eigen::half>
{
enum {
IsSigned = true,
IsInteger = false,
IsComplex = false,
RequireInitialization = false
};
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half epsilon() {
return half_impl::raw_uint16_to_half(0x0800);
}
@@ -507,7 +592,7 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half exph(const Eigen::half& a) {
return Eigen::half(::expf(float(a)));
}
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half logh(const Eigen::half& a) {
#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
#if EIGEN_CUDACC_VER >= 80000 && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530
return Eigen::half(::hlog(a));
#else
return Eigen::half(::logf(float(a)));
@@ -541,14 +626,18 @@ struct hash<Eigen::half> {
// Add the missing shfl_xor intrinsic
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
#if defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 300
__device__ EIGEN_STRONG_INLINE Eigen::half __shfl_xor(Eigen::half var, int laneMask, int width=warpSize) {
#if EIGEN_CUDACC_VER < 90000
return static_cast<Eigen::half>(__shfl_xor(static_cast<float>(var), laneMask, width));
#else
return static_cast<Eigen::half>(__shfl_xor_sync(0xFFFFFFFF, static_cast<float>(var), laneMask, width));
#endif
}
#endif
// ldg() has an overload for __half, but we also need one for Eigen::half.
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
// ldg() has an overload for __half_raw, but we also need one for Eigen::half.
#if defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 350
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half __ldg(const Eigen::half* ptr) {
return Eigen::half_impl::raw_uint16_to_half(
__ldg(reinterpret_cast<const unsigned short*>(ptr)));
@@ -556,7 +645,7 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half __ldg(const Eigen::half* ptr)
#endif
#if defined(__CUDA_ARCH__)
#if defined(EIGEN_CUDA_ARCH)
namespace Eigen {
namespace numext {

View File

@@ -291,7 +291,7 @@ template<> EIGEN_DEVICE_FUNC inline double2 pabs<double2>(const double2& a) {
EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<float4,4>& kernel) {
double tmp = kernel.packet[0].y;
float tmp = kernel.packet[0].y;
kernel.packet[0].y = kernel.packet[1].x;
kernel.packet[1].x = tmp;

View File

@@ -99,7 +99,8 @@ template<> __device__ EIGEN_STRONG_INLINE Eigen::half pfirst<half2>(const half2&
template<> __device__ EIGEN_STRONG_INLINE half2 pabs<half2>(const half2& a) {
half2 result;
result.x = a.x & 0x7FFF7FFF;
unsigned temp = *(reinterpret_cast<const unsigned*>(&(a)));
*(reinterpret_cast<unsigned*>(&(result))) = temp & 0x7FFF7FFF;
return result;
}
@@ -275,7 +276,7 @@ template<> __device__ EIGEN_STRONG_INLINE half2 plog1p<half2>(const half2& a) {
return __floats2half2_rn(r1, r2);
}
#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 530
#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530
template<> __device__ EIGEN_STRONG_INLINE
half2 plog<half2>(const half2& a) {

View File

@@ -0,0 +1,29 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2017 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_ARCH_CONJ_HELPER_H
#define EIGEN_ARCH_CONJ_HELPER_H
#define EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(PACKET_CPLX, PACKET_REAL) \
template<> struct conj_helper<PACKET_REAL, PACKET_CPLX, false,false> { \
EIGEN_STRONG_INLINE PACKET_CPLX pmadd(const PACKET_REAL& x, const PACKET_CPLX& y, const PACKET_CPLX& c) const \
{ return padd(c, pmul(x,y)); } \
EIGEN_STRONG_INLINE PACKET_CPLX pmul(const PACKET_REAL& x, const PACKET_CPLX& y) const \
{ return PACKET_CPLX(Eigen::internal::pmul<PACKET_REAL>(x, y.v)); } \
}; \
\
template<> struct conj_helper<PACKET_CPLX, PACKET_REAL, false,false> { \
EIGEN_STRONG_INLINE PACKET_CPLX pmadd(const PACKET_CPLX& x, const PACKET_REAL& y, const PACKET_CPLX& c) const \
{ return padd(c, pmul(x,y)); } \
EIGEN_STRONG_INLINE PACKET_CPLX pmul(const PACKET_CPLX& x, const PACKET_REAL& y) const \
{ return PACKET_CPLX(Eigen::internal::pmul<PACKET_REAL>(x.v, y)); } \
};
#endif // EIGEN_ARCH_CONJ_HELPER_H

View File

@@ -67,7 +67,7 @@ template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type;
template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>& from)
{
float32x2_t r64;
r64 = vld1_f32((float *)&from);
r64 = vld1_f32((const float *)&from);
return Packet2cf(vcombine_f32(r64, r64));
}
@@ -142,7 +142,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf
to[stride*1] = std::complex<float>(vgetq_lane_f32(from.v, 2), vgetq_lane_f32(from.v, 3));
}
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ARM_PREFETCH((float *)addr); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ARM_PREFETCH((const float *)addr); }
template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a)
{
@@ -265,6 +265,8 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true>
}
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
{
// TODO optimize it for NEON
@@ -275,7 +277,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, con
s = vmulq_f32(b.v, b.v);
rev_s = vrev64q_f32(s);
return Packet2cf(pdiv(res.v, vaddq_f32(s,rev_s)));
return Packet2cf(pdiv<Packet4f>(res.v, vaddq_f32(s,rev_s)));
}
EIGEN_DEVICE_FUNC inline void
@@ -381,7 +383,7 @@ template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { EIGEN_ARM_PREFETCH((double *)addr); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { EIGEN_ARM_PREFETCH((const double *)addr); }
template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride)
{
@@ -456,6 +458,8 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
}
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
{
// TODO optimize it for NEON

View File

@@ -28,11 +28,42 @@ namespace internal {
#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
#endif
// FIXME NEON has 16 quad registers, but since the current register allocator
// is so bad, it is much better to reduce it to 8
#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
#if EIGEN_ARCH_ARM64
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 32
#else
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 16
#endif
#endif
#if EIGEN_COMP_MSVC
// In MSVC's arm_neon.h header file, all NEON vector types
// are aliases to the same underlying type __n128.
// We thus have to wrap them to make them different C++ types.
// (See also bug 1428)
template<typename T,int unique_id>
struct eigen_packet_wrapper
{
operator T&() { return m_val; }
operator const T&() const { return m_val; }
eigen_packet_wrapper() {}
eigen_packet_wrapper(const T &v) : m_val(v) {}
eigen_packet_wrapper& operator=(const T &v) {
m_val = v;
return *this;
}
T m_val;
};
typedef eigen_packet_wrapper<float32x2_t,0> Packet2f;
typedef eigen_packet_wrapper<float32x4_t,1> Packet4f;
typedef eigen_packet_wrapper<int32x4_t ,2> Packet4i;
typedef eigen_packet_wrapper<int32x2_t ,3> Packet2i;
typedef eigen_packet_wrapper<uint32x4_t ,4> Packet4ui;
#else
typedef float32x2_t Packet2f;
typedef float32x4_t Packet4f;
@@ -40,23 +71,28 @@ typedef int32x4_t Packet4i;
typedef int32x2_t Packet2i;
typedef uint32x4_t Packet4ui;
#endif // EIGEN_COMP_MSVC
#define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
const Packet4f p4f_##NAME = pset1<Packet4f>(X)
#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
const Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int>(X))
const Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int32_t>(X))
#define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
const Packet4i p4i_##NAME = pset1<Packet4i>(X)
// arm64 does have the pld instruction. If available, let's trust the __builtin_prefetch built-in function
// which available on LLVM and GCC (at least)
#if EIGEN_HAS_BUILTIN(__builtin_prefetch) || EIGEN_COMP_GNUC
#if EIGEN_ARCH_ARM64
// __builtin_prefetch tends to do nothing on ARM64 compilers because the
// prefetch instructions there are too detailed for __builtin_prefetch to map
// meaningfully to them.
#define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__("prfm pldl1keep, [%[addr]]\n" ::[addr] "r"(ADDR) : );
#elif EIGEN_HAS_BUILTIN(__builtin_prefetch) || EIGEN_COMP_GNUC
#define EIGEN_ARM_PREFETCH(ADDR) __builtin_prefetch(ADDR);
#elif defined __pld
#define EIGEN_ARM_PREFETCH(ADDR) __pld(ADDR)
#elif !EIGEN_ARCH_ARM64
#define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__ ( " pld [%[addr]]\n" :: [addr] "r" (ADDR) : "cc" );
#elif EIGEN_ARCH_ARM32
#define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__ ("pld [%[addr]]\n" :: [addr] "r" (ADDR) : );
#else
// by default no explicit prefetching
#define EIGEN_ARM_PREFETCH(ADDR)
@@ -81,7 +117,7 @@ template<> struct packet_traits<float> : default_packet_traits
HasSqrt = 0
};
};
template<> struct packet_traits<int> : default_packet_traits
template<> struct packet_traits<int32_t> : default_packet_traits
{
typedef Packet4i type;
typedef Packet4i half; // Packet2i intrinsics not implemented yet
@@ -103,19 +139,19 @@ EIGEN_STRONG_INLINE void vst1q_f32(float* to, float32x4_t from) { ::vst1q
EIGEN_STRONG_INLINE void vst1_f32 (float* to, float32x2_t from) { ::vst1_f32 ((float32_t*)to,from); }
#endif
template<> struct unpacket_traits<Packet4f> { typedef float type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
template<> struct unpacket_traits<Packet4i> { typedef int type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
template<> struct unpacket_traits<Packet4f> { typedef float type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
template<> struct unpacket_traits<Packet4i> { typedef int32_t type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float& from) { return vdupq_n_f32(from); }
template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int& from) { return vdupq_n_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int32_t& from) { return vdupq_n_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a)
{
const float32_t f[] = {0, 1, 2, 3};
const float f[] = {0, 1, 2, 3};
Packet4f countdown = vld1q_f32(f);
return vaddq_f32(pset1<Packet4f>(a), countdown);
}
template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a)
template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int32_t& a)
{
const int32_t i[] = {0, 1, 2, 3};
Packet4i countdown = vld1q_s32(i);
@@ -238,20 +274,20 @@ template<> EIGEN_STRONG_INLINE Packet4f pandnot<Packet4f>(const Packet4f& a, con
}
template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return vbicq_s32(a,b); }
template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_f32(from); }
template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_f32(from); }
template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int32_t* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_f32(from); }
template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_f32(from); }
template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int32_t* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_s32(from); }
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
{
float32x2_t lo, hi;
lo = vld1_dup_f32(from);
hi = vld1_dup_f32(from+1);
return vcombine_f32(lo, hi);
}
template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int* from)
template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int32_t* from)
{
int32x2_t lo, hi;
lo = vld1_dup_s32(from);
@@ -259,11 +295,11 @@ template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int* from)
return vcombine_s32(lo, hi);
}
template<> EIGEN_STRONG_INLINE void pstore<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_f32(to, from); }
template<> EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_s32(to, from); }
template<> EIGEN_STRONG_INLINE void pstore<float> (float* to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_f32(to, from); }
template<> EIGEN_STRONG_INLINE void pstore<int32_t>(int32_t* to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_s32(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<float> (float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<int32_t>(int32_t* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
{
@@ -274,7 +310,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const floa
res = vsetq_lane_f32(from[3*stride], res, 3);
return res;
}
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, Index stride)
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int32_t, Packet4i>(const int32_t* from, Index stride)
{
Packet4i res = pset1<Packet4i>(0);
res = vsetq_lane_s32(from[0*stride], res, 0);
@@ -291,7 +327,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, co
to[stride*2] = vgetq_lane_f32(from, 2);
to[stride*3] = vgetq_lane_f32(from, 3);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, Index stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<int32_t, Packet4i>(int32_t* to, const Packet4i& from, Index stride)
{
to[stride*0] = vgetq_lane_s32(from, 0);
to[stride*1] = vgetq_lane_s32(from, 1);
@@ -299,12 +335,12 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const
to[stride*3] = vgetq_lane_s32(from, 3);
}
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { EIGEN_ARM_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { EIGEN_ARM_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<float> (const float* addr) { EIGEN_ARM_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<int32_t>(const int32_t* addr) { EIGEN_ARM_PREFETCH(addr); }
// FIXME only store the 2 first elements ?
template<> EIGEN_STRONG_INLINE float pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE int pfirst<Packet4i>(const Packet4i& a) { int EIGEN_ALIGN16 x[4]; vst1q_s32(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE float pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE int32_t pfirst<Packet4i>(const Packet4i& a) { int32_t EIGEN_ALIGN16 x[4]; vst1q_s32(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a) {
float32x2_t a_lo, a_hi;
@@ -359,7 +395,7 @@ template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
return sum;
}
template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
template<> EIGEN_STRONG_INLINE int32_t predux<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, sum;
@@ -406,7 +442,7 @@ template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
return vget_lane_f32(prod, 0);
}
template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
template<> EIGEN_STRONG_INLINE int32_t predux_mul<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, prod;
@@ -434,7 +470,7 @@ template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
return vget_lane_f32(min, 0);
}
template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
template<> EIGEN_STRONG_INLINE int32_t predux_min<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, min;
@@ -459,7 +495,7 @@ template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
return vget_lane_f32(max, 0);
}
template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
template<> EIGEN_STRONG_INLINE int32_t predux_max<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, max;

View File

@@ -128,7 +128,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf
_mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 3)));
}
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a)
{
@@ -229,23 +229,7 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true>
}
};
template<> struct conj_helper<Packet4f, Packet2cf, false,false>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const
{ return Packet2cf(Eigen::internal::pmul<Packet4f>(x, y.v)); }
};
template<> struct conj_helper<Packet2cf, Packet4f, false,false>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const
{ return Packet2cf(Eigen::internal::pmul<Packet4f>(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
{
@@ -340,7 +324,7 @@ template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, Packet2d(from.v)); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, Packet2d(from.v)); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet1cd>(const Packet1cd& a)
{
@@ -430,23 +414,7 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
}
};
template<> struct conj_helper<Packet2d, Packet1cd, false,false>
{
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const
{ return Packet1cd(Eigen::internal::pmul<Packet2d>(x, y.v)); }
};
template<> struct conj_helper<Packet1cd, Packet2d, false,false>
{
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const
{ return Packet1cd(Eigen::internal::pmul<Packet2d>(x.v, y)); }
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
{

View File

@@ -28,7 +28,7 @@ namespace internal {
#endif
#endif
#if (defined EIGEN_VECTORIZE_AVX) && EIGEN_COMP_GNUC_STRICT && (__GXX_ABI_VERSION < 1004)
#if ((defined EIGEN_VECTORIZE_AVX) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_MINGW) && (__GXX_ABI_VERSION < 1004)) || EIGEN_OS_QNX
// With GCC's default ABI version, a __m128 or __m256 are the same types and therefore we cannot
// have overloads for both types without linking error.
// One solution is to increase ABI version using -fabi-version=4 (or greater).
@@ -409,10 +409,16 @@ template<> EIGEN_STRONG_INLINE void pstore1<Packet2d>(double* to, const double&
pstore(to, Packet2d(vec2d_swizzle1(pa,0,0)));
}
#if EIGEN_COMP_PGI
typedef const void * SsePrefetchPtrType;
#else
typedef const char * SsePrefetchPtrType;
#endif
#ifndef EIGEN_VECTORIZE_AVX
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); }
#endif
#if EIGEN_COMP_MSVC_STRICT && EIGEN_OS_WIN64
@@ -504,30 +510,13 @@ template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
{
return _mm_hadd_ps(_mm_hadd_ps(vecs[0], vecs[1]),_mm_hadd_ps(vecs[2], vecs[3]));
}
template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
{
return _mm_hadd_pd(vecs[0], vecs[1]);
}
template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
{
Packet4f tmp0 = _mm_hadd_ps(a,a);
return pfirst<Packet4f>(_mm_hadd_ps(tmp0, tmp0));
}
template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a) { return pfirst<Packet2d>(_mm_hadd_pd(a, a)); }
#else
// SSE2 versions
template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
{
Packet4f tmp = _mm_add_ps(a, _mm_movehl_ps(a,a));
return pfirst<Packet4f>(_mm_add_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
}
template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
{
return pfirst<Packet2d>(_mm_add_sd(a, _mm_unpackhi_pd(a,a)));
}
template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
{
Packet4f tmp0, tmp1, tmp2;
@@ -548,6 +537,29 @@ template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
}
#endif // SSE3
template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
{
// Disable SSE3 _mm_hadd_pd that is extremely slow on all existing Intel's architectures
// (from Nehalem to Haswell)
// #ifdef EIGEN_VECTORIZE_SSE3
// Packet4f tmp = _mm_add_ps(a, vec4f_swizzle1(a,2,3,2,3));
// return pfirst<Packet4f>(_mm_hadd_ps(tmp, tmp));
// #else
Packet4f tmp = _mm_add_ps(a, _mm_movehl_ps(a,a));
return pfirst<Packet4f>(_mm_add_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
// #endif
}
template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
{
// Disable SSE3 _mm_hadd_pd that is extremely slow on all existing Intel's architectures
// (from Nehalem to Haswell)
// #ifdef EIGEN_VECTORIZE_SSE3
// return pfirst<Packet2d>(_mm_hadd_pd(a, a));
// #else
return pfirst<Packet2d>(_mm_add_sd(a, _mm_unpackhi_pd(a,a)));
// #endif
}
#ifdef EIGEN_VECTORIZE_SSSE3
template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
@@ -870,4 +882,14 @@ template<> EIGEN_STRONG_INLINE double pmadd(const double& a, const double& b, co
} // end namespace Eigen
#if EIGEN_COMP_PGI
// PGI++ does not define the following intrinsics in C++ mode.
static inline __m128 _mm_castpd_ps (__m128d x) { return reinterpret_cast<__m128&>(x); }
static inline __m128i _mm_castpd_si128(__m128d x) { return reinterpret_cast<__m128i&>(x); }
static inline __m128d _mm_castps_pd (__m128 x) { return reinterpret_cast<__m128d&>(x); }
static inline __m128i _mm_castps_si128(__m128 x) { return reinterpret_cast<__m128i&>(x); }
static inline __m128 _mm_castsi128_ps(__m128i x) { return reinterpret_cast<__m128&>(x); }
static inline __m128d _mm_castsi128_pd(__m128i x) { return reinterpret_cast<__m128d&>(x); }
#endif
#endif // EIGEN_PACKET_MATH_SSE_H

View File

@@ -14,6 +14,7 @@ namespace Eigen {
namespace internal {
#ifndef EIGEN_VECTORIZE_AVX
template <>
struct type_casting_traits<float, int> {
enum {
@@ -23,11 +24,6 @@ struct type_casting_traits<float, int> {
};
};
template<> EIGEN_STRONG_INLINE Packet4i pcast<Packet4f, Packet4i>(const Packet4f& a) {
return _mm_cvttps_epi32(a);
}
template <>
struct type_casting_traits<int, float> {
enum {
@@ -37,11 +33,6 @@ struct type_casting_traits<int, float> {
};
};
template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4i, Packet4f>(const Packet4i& a) {
return _mm_cvtepi32_ps(a);
}
template <>
struct type_casting_traits<double, float> {
enum {
@@ -51,10 +42,6 @@ struct type_casting_traits<double, float> {
};
};
template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet2d, Packet4f>(const Packet2d& a, const Packet2d& b) {
return _mm_shuffle_ps(_mm_cvtpd_ps(a), _mm_cvtpd_ps(b), (1 << 2) | (1 << 6));
}
template <>
struct type_casting_traits<float, double> {
enum {
@@ -63,6 +50,19 @@ struct type_casting_traits<float, double> {
TgtCoeffRatio = 2
};
};
#endif
template<> EIGEN_STRONG_INLINE Packet4i pcast<Packet4f, Packet4i>(const Packet4f& a) {
return _mm_cvttps_epi32(a);
}
template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4i, Packet4f>(const Packet4i& a) {
return _mm_cvtepi32_ps(a);
}
template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet2d, Packet4f>(const Packet2d& a, const Packet2d& b) {
return _mm_shuffle_ps(_mm_cvtpd_ps(a), _mm_cvtpd_ps(b), (1 << 2) | (1 << 6));
}
template<> EIGEN_STRONG_INLINE Packet2d pcast<Packet4f, Packet2d>(const Packet4f& a) {
// Simply discard the second half of the input

View File

@@ -2,6 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -24,13 +25,48 @@ struct Packet1cd
Packet2d v;
};
struct Packet2cf
{
EIGEN_STRONG_INLINE Packet2cf() {}
EIGEN_STRONG_INLINE explicit Packet2cf(const Packet4f& a) : v(a) {}
union {
Packet4f v;
Packet1cd cd[2];
};
};
template<> struct packet_traits<std::complex<float> > : default_packet_traits
{
typedef Packet2cf type;
typedef Packet2cf half;
enum {
Vectorizable = 1,
AlignedOnScalar = 1,
size = 2,
HasHalfPacket = 0,
HasAdd = 1,
HasSub = 1,
HasMul = 1,
HasDiv = 1,
HasNegate = 1,
HasAbs = 0,
HasAbs2 = 0,
HasMin = 0,
HasMax = 0,
HasBlend = 1,
HasSetLinear = 0
};
};
template<> struct packet_traits<std::complex<double> > : default_packet_traits
{
typedef Packet1cd type;
typedef Packet1cd half;
enum {
Vectorizable = 1,
AlignedOnScalar = 0,
AlignedOnScalar = 1,
size = 1,
HasHalfPacket = 0,
@@ -47,20 +83,68 @@ template<> struct packet_traits<std::complex<double> > : default_packet_traits
};
};
template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
/* Forward declaration */
EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel);
template<> EIGEN_STRONG_INLINE Packet2cf pload <Packet2cf>(const std::complex<float>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet2cf(pload<Packet4f>((const float*)from)); }
template<> EIGEN_STRONG_INLINE Packet1cd pload <Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet1cd(pload<Packet2d>((const double*)from)); }
template<> EIGEN_STRONG_INLINE Packet2cf ploadu<Packet2cf>(const std::complex<float>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet2cf(ploadu<Packet4f>((const float*)from)); }
template<> EIGEN_STRONG_INLINE Packet1cd ploadu<Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet1cd(ploadu<Packet2d>((const double*)from)); }
template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> * to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> * to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE Packet1cd pset1<Packet1cd>(const std::complex<double>& from)
{ /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>& from)
{
Packet2cf res;
res.cd[0] = Packet1cd(vec_ld2f((const float *)&from));
res.cd[1] = res.cd[0];
return res;
}
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
{
std::complex<float> EIGEN_ALIGN16 af[2];
af[0] = from[0*stride];
af[1] = from[1*stride];
return pload<Packet2cf>(af);
}
template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride EIGEN_UNUSED)
{
return pload<Packet1cd>(from);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
{
std::complex<float> EIGEN_ALIGN16 af[2];
pstore<std::complex<float> >((std::complex<float> *) af, from);
to[0*stride] = af[0];
to[1*stride] = af[1];
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet1cd>(std::complex<double>* to, const Packet1cd& from, Index stride EIGEN_UNUSED)
{
pstore<std::complex<double> >(to, from);
}
template<> EIGEN_STRONG_INLINE Packet2cf padd<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(padd<Packet4f>(a.v, b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v + b.v); }
template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(psub<Packet4f>(a.v, b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v - b.v); }
template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(Packet2d(a.v))); }
template<> EIGEN_STRONG_INLINE Packet2cf pnegate(const Packet2cf& a) { return Packet2cf(pnegate(Packet4f(a.v))); }
template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a) { return Packet1cd((Packet2d)vec_xor((Packet2d)a.v, (Packet2d)p2ul_CONJ_XOR2)); }
template<> EIGEN_STRONG_INLINE Packet2cf pconj(const Packet2cf& a)
{
Packet2cf res;
res.v.v4f[0] = pconj(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[0]))).v;
res.v.v4f[1] = pconj(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[1]))).v;
return res;
}
template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
{
@@ -79,43 +163,90 @@ template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, con
return Packet1cd(v1 + v2);
}
template<> EIGEN_STRONG_INLINE Packet1cd pand <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd por <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_or(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd pxor <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_xor(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v, vec_nor(b.v,b.v))); }
template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>* from)
template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
{
return pset1<Packet1cd>(*from);
Packet2cf res;
res.v.v4f[0] = pmul(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[0])), Packet1cd(reinterpret_cast<Packet2d>(b.v.v4f[0]))).v;
res.v.v4f[1] = pmul(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[1])), Packet1cd(reinterpret_cast<Packet2d>(b.v.v4f[1]))).v;
return res;
}
template<> EIGEN_STRONG_INLINE Packet1cd pand <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cf pand <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pand<Packet4f>(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd por <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_or(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cf por <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(por<Packet4f>(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd pxor <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_xor(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cf pxor <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pxor<Packet4f>(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v, vec_nor(b.v,b.v))); }
template<> EIGEN_STRONG_INLINE Packet2cf pandnot<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pandnot<Packet4f>(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>* from) { return pset1<Packet1cd>(*from); }
template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>* from) { return pset1<Packet2cf>(*from); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet1cd>(const Packet1cd& a)
{
std::complex<double> EIGEN_ALIGN16 res[2];
pstore<std::complex<double> >(res, a);
std::complex<double> EIGEN_ALIGN16 res;
pstore<std::complex<double> >(&res, a);
return res;
}
template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a)
{
std::complex<float> EIGEN_ALIGN16 res[2];
pstore<std::complex<float> >(res, a);
return res[0];
}
template<> EIGEN_STRONG_INLINE Packet1cd preverse(const Packet1cd& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a)
{
Packet2cf res;
res.cd[0] = a.cd[1];
res.cd[1] = a.cd[0];
return res;
}
template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet1cd>(const Packet1cd& a)
{
return pfirst(a);
}
template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet2cf>(const Packet2cf& a)
{
std::complex<float> res;
Packet1cd b = padd<Packet1cd>(a.cd[0], a.cd[1]);
vec_st2f(b.v, (float*)&res);
return res;
}
template<> EIGEN_STRONG_INLINE Packet1cd preduxp<Packet1cd>(const Packet1cd* vecs)
{
return vecs[0];
}
template<> EIGEN_STRONG_INLINE Packet2cf preduxp<Packet2cf>(const Packet2cf* vecs)
{
PacketBlock<Packet2cf,2> transpose;
transpose.packet[0] = vecs[0];
transpose.packet[1] = vecs[1];
ptranspose(transpose);
return padd<Packet2cf>(transpose.packet[0], transpose.packet[1]);
}
template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const Packet1cd& a)
{
return pfirst(a);
}
template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const Packet2cf& a)
{
std::complex<float> res;
Packet1cd b = pmul<Packet1cd>(a.cd[0], a.cd[1]);
vec_st2f(b.v, (float*)&res);
return res;
}
template<int Offset>
struct palign_impl<Offset,Packet1cd>
@@ -127,6 +258,18 @@ struct palign_impl<Offset,Packet1cd>
}
};
template<int Offset>
struct palign_impl<Offset,Packet2cf>
{
static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
{
if (Offset == 1) {
first.cd[0] = first.cd[1];
first.cd[1] = second.cd[0];
}
}
};
template<> struct conj_helper<Packet1cd, Packet1cd, false,true>
{
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
@@ -160,6 +303,42 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
}
};
template<> struct conj_helper<Packet2cf, Packet2cf, false,true>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
{
return internal::pmul(a, pconj(b));
}
};
template<> struct conj_helper<Packet2cf, Packet2cf, true,false>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
{
return internal::pmul(pconj(a), b);
}
};
template<> struct conj_helper<Packet2cf, Packet2cf, true,true>
{
EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
{
return pconj(internal::pmul(a, b));
}
};
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
{
// TODO optimize it for AltiVec
@@ -168,17 +347,49 @@ template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, con
return Packet1cd(pdiv(res.v, s + vec_perm(s, s, p16uc_REVERSE64)));
}
template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
{
// TODO optimize it for AltiVec
Packet2cf res;
res.cd[0] = pdiv<Packet1cd>(a.cd[0], b.cd[0]);
res.cd[1] = pdiv<Packet1cd>(a.cd[1], b.cd[1]);
return res;
}
EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
{
return Packet1cd(preverse(Packet2d(x.v)));
}
EIGEN_STRONG_INLINE Packet2cf pcplxflip/*<Packet2cf>*/(const Packet2cf& x)
{
Packet2cf res;
res.cd[0] = pcplxflip(x.cd[0]);
res.cd[1] = pcplxflip(x.cd[1]);
return res;
}
EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet1cd,2>& kernel)
{
Packet2d tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
kernel.packet[0].v = tmp;
}
EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel)
{
Packet1cd tmp = kernel.packet[0].cd[1];
kernel.packet[0].cd[1] = kernel.packet[1].cd[0];
kernel.packet[1].cd[0] = tmp;
}
template<> EIGEN_STRONG_INLINE Packet2cf pblend(const Selector<2>& ifPacket, const Packet2cf& thenPacket, const Packet2cf& elsePacket) {
Packet2cf result;
const Selector<4> ifPacket4 = { ifPacket.select[0], ifPacket.select[0], ifPacket.select[1], ifPacket.select[1] };
result.v = pblend<Packet4f>(ifPacket4, thenPacket.v, elsePacket.v);
return result;
}
} // end namespace internal
} // end namespace Eigen

View File

@@ -3,6 +3,7 @@
//
// Copyright (C) 2007 Julien Pommier
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -19,32 +20,32 @@ namespace Eigen {
namespace internal {
static _EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
static _EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
static _EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
static _EIGEN_DECLARE_CONST_Packet2d(exp_hi, 709.437);
static _EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet2d pexp<Packet2d>(const Packet2d& _x)
{
Packet2d x = _x;
_EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
_EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
_EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
_EIGEN_DECLARE_CONST_Packet2d(exp_hi, 709.437);
_EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
_EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
Packet2d tmp, fx;
Packet2l emm0;
@@ -91,18 +92,44 @@ Packet2d pexp<Packet2d>(const Packet2d& _x)
isnumber_mask);
}
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet4f pexp<Packet4f>(const Packet4f& x)
{
Packet4f res;
res.v4f[0] = pexp<Packet2d>(x.v4f[0]);
res.v4f[1] = pexp<Packet2d>(x.v4f[1]);
return res;
}
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet2d psqrt<Packet2d>(const Packet2d& x)
{
return __builtin_s390_vfsqdb(x);
}
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet4f psqrt<Packet4f>(const Packet4f& x)
{
Packet4f res;
res.v4f[0] = psqrt<Packet2d>(x.v4f[0]);
res.v4f[1] = psqrt<Packet2d>(x.v4f[1]);
return res;
}
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet2d prsqrt<Packet2d>(const Packet2d& x) {
// Unfortunately we can't use the much faster mm_rqsrt_pd since it only provides an approximation.
return pset1<Packet2d>(1.0) / psqrt<Packet2d>(x);
}
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
Packet4f prsqrt<Packet4f>(const Packet4f& x) {
Packet4f res;
res.v4f[0] = prsqrt<Packet2d>(x.v4f[0]);
res.v4f[1] = prsqrt<Packet2d>(x.v4f[1]);
return res;
}
} // end namespace internal
} // end namespace Eigen

View File

@@ -28,9 +28,8 @@ namespace internal {
#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
#endif
// NOTE Altivec has 32 registers, but Eigen only accepts a value of 8 or 16
#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 32
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 16
#endif
typedef __vector int Packet4i;
@@ -42,6 +41,10 @@ typedef __vector double Packet2d;
typedef __vector unsigned long long Packet2ul;
typedef __vector long long Packet2l;
typedef struct {
Packet2d v4f[2];
} Packet4f;
typedef union {
int32_t i[4];
uint32_t ui[4];
@@ -88,6 +91,7 @@ static Packet2d p2d_ONE = { 1.0, 1.0 };
static Packet2d p2d_ZERO_ = { -0.0, -0.0 };
static Packet4i p4i_COUNTDOWN = { 0, 1, 2, 3 };
static Packet4f p4f_COUNTDOWN = { 0.0, 1.0, 2.0, 3.0 };
static Packet2d p2d_COUNTDOWN = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet16uc>(p2d_ZERO), reinterpret_cast<Packet16uc>(p2d_ONE), 8));
static Packet16uc p16uc_PSET64_HI = { 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
@@ -96,7 +100,7 @@ static Packet16uc p16uc_DUPLICATE32_HI = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7 };
// Mask alignment
#define _EIGEN_MASK_ALIGNMENT 0xfffffffffffffff0
#define _EIGEN_ALIGNED_PTR(x) ((ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
#define _EIGEN_ALIGNED_PTR(x) ((std::ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
// Handle endianness properly while loading constants
// Define global static constants:
@@ -132,13 +136,11 @@ template<> struct packet_traits<int> : default_packet_traits
typedef Packet4i type;
typedef Packet4i half;
enum {
// FIXME check the Has*
Vectorizable = 1,
AlignedOnScalar = 1,
size = 4,
HasHalfPacket = 0,
// FIXME check the Has*
HasAdd = 1,
HasSub = 1,
HasMul = 1,
@@ -147,6 +149,37 @@ template<> struct packet_traits<int> : default_packet_traits
};
};
template<> struct packet_traits<float> : default_packet_traits
{
typedef Packet4f type;
typedef Packet4f half;
enum {
Vectorizable = 1,
AlignedOnScalar = 1,
size=4,
HasHalfPacket = 0,
HasAdd = 1,
HasSub = 1,
HasMul = 1,
HasDiv = 1,
HasMin = 1,
HasMax = 1,
HasAbs = 1,
HasSin = 0,
HasCos = 0,
HasLog = 0,
HasExp = 1,
HasSqrt = 1,
HasRsqrt = 1,
HasRound = 1,
HasFloor = 1,
HasCeil = 1,
HasNegate = 1,
HasBlend = 1
};
};
template<> struct packet_traits<double> : default_packet_traits
{
typedef Packet2d type;
@@ -157,7 +190,6 @@ template<> struct packet_traits<double> : default_packet_traits
size=2,
HasHalfPacket = 1,
// FIXME check the Has*
HasAdd = 1,
HasSub = 1,
HasMul = 1,
@@ -180,8 +212,12 @@ template<> struct packet_traits<double> : default_packet_traits
};
template<> struct unpacket_traits<Packet4i> { typedef int type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
template<> struct unpacket_traits<Packet4f> { typedef float type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
/* Forward declaration */
EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet4f,4>& kernel);
inline std::ostream & operator <<(std::ostream & s, const Packet4i & v)
{
Packet vt;
@@ -222,6 +258,32 @@ inline std::ostream & operator <<(std::ostream & s, const Packet2d & v)
return s;
}
/* Helper function to simulate a vec_splat_packet4f
*/
template<int element> EIGEN_STRONG_INLINE Packet4f vec_splat_packet4f(const Packet4f& from)
{
Packet4f splat;
switch (element) {
case 0:
splat.v4f[0] = vec_splat(from.v4f[0], 0);
splat.v4f[1] = splat.v4f[0];
break;
case 1:
splat.v4f[0] = vec_splat(from.v4f[0], 1);
splat.v4f[1] = splat.v4f[0];
break;
case 2:
splat.v4f[0] = vec_splat(from.v4f[1], 0);
splat.v4f[1] = splat.v4f[0];
break;
case 3:
splat.v4f[0] = vec_splat(from.v4f[1], 1);
splat.v4f[1] = splat.v4f[0];
break;
}
return splat;
}
template<int Offset>
struct palign_impl<Offset,Packet4i>
{
@@ -238,6 +300,31 @@ struct palign_impl<Offset,Packet4i>
}
};
/* This is a tricky one, we have to translate float alignment to vector elements of sizeof double
*/
template<int Offset>
struct palign_impl<Offset,Packet4f>
{
static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
{
switch (Offset % 4) {
case 1:
first.v4f[0] = vec_sld(first.v4f[0], first.v4f[1], 8);
first.v4f[1] = vec_sld(first.v4f[1], second.v4f[0], 8);
break;
case 2:
first.v4f[0] = first.v4f[1];
first.v4f[1] = second.v4f[0];
break;
case 3:
first.v4f[0] = vec_sld(first.v4f[1], second.v4f[0], 8);
first.v4f[1] = vec_sld(second.v4f[0], second.v4f[1], 8);
break;
}
}
};
template<int Offset>
struct palign_impl<Offset,Packet2d>
{
@@ -257,6 +344,16 @@ template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int* from)
return vfrom->v4i;
}
template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from)
{
// FIXME: No intrinsic yet
EIGEN_DEBUG_ALIGNED_LOAD
Packet4f vfrom;
vfrom.v4f[0] = vec_ld2f(&from[0]);
vfrom.v4f[1] = vec_ld2f(&from[2]);
return vfrom;
}
template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double* from)
{
// FIXME: No intrinsic yet
@@ -275,6 +372,15 @@ template<> EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet4i& f
vto->v4i = from;
}
template<> EIGEN_STRONG_INLINE void pstore<float>(float* to, const Packet4f& from)
{
// FIXME: No intrinsic yet
EIGEN_DEBUG_ALIGNED_STORE
vec_st2f(from.v4f[0], &to[0]);
vec_st2f(from.v4f[1], &to[2]);
}
template<> EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet2d& from)
{
// FIXME: No intrinsic yet
@@ -288,10 +394,16 @@ template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int& from)
{
return vec_splats(from);
}
template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) {
return vec_splats(from);
}
template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float& from)
{
Packet4f to;
to.v4f[0] = pset1<Packet2d>(static_cast<const double&>(from));
to.v4f[1] = to.v4f[0];
return to;
}
template<> EIGEN_STRONG_INLINE void
pbroadcast4<Packet4i>(const int *a,
@@ -304,6 +416,17 @@ pbroadcast4<Packet4i>(const int *a,
a3 = vec_splat(a3, 3);
}
template<> EIGEN_STRONG_INLINE void
pbroadcast4<Packet4f>(const float *a,
Packet4f& a0, Packet4f& a1, Packet4f& a2, Packet4f& a3)
{
a3 = pload<Packet4f>(a);
a0 = vec_splat_packet4f<0>(a3);
a1 = vec_splat_packet4f<1>(a3);
a2 = vec_splat_packet4f<2>(a3);
a3 = vec_splat_packet4f<3>(a3);
}
template<> EIGEN_STRONG_INLINE void
pbroadcast4<Packet2d>(const double *a,
Packet2d& a0, Packet2d& a1, Packet2d& a2, Packet2d& a3)
@@ -326,6 +449,16 @@ template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* f
return pload<Packet4i>(ai);
}
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
{
float EIGEN_ALIGN16 ai[4];
ai[0] = from[0*stride];
ai[1] = from[1*stride];
ai[2] = from[2*stride];
ai[3] = from[3*stride];
return pload<Packet4f>(ai);
}
template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
{
double EIGEN_ALIGN16 af[2];
@@ -344,6 +477,16 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const
to[3*stride] = ai[3];
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
{
float EIGEN_ALIGN16 ai[4];
pstore<float>((float *)ai, from);
to[0*stride] = ai[0];
to[1*stride] = ai[1];
to[2*stride] = ai[2];
to[3*stride] = ai[3];
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
{
double EIGEN_ALIGN16 af[2];
@@ -353,52 +496,160 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to,
}
template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a + b); }
template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f c;
c.v4f[0] = a.v4f[0] + b.v4f[0];
c.v4f[1] = a.v4f[1] + b.v4f[1];
return c;
}
template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a + b); }
template<> EIGEN_STRONG_INLINE Packet4i psub<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a - b); }
template<> EIGEN_STRONG_INLINE Packet4f psub<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f c;
c.v4f[0] = a.v4f[0] - b.v4f[0];
c.v4f[1] = a.v4f[1] - b.v4f[1];
return c;
}
template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a - b); }
template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a * b); }
template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f c;
c.v4f[0] = a.v4f[0] * b.v4f[0];
c.v4f[1] = a.v4f[1] * b.v4f[1];
return c;
}
template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a * b); }
template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a / b); }
template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f c;
c.v4f[0] = a.v4f[0] / b.v4f[0];
c.v4f[1] = a.v4f[1] / b.v4f[1];
return c;
}
template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a / b); }
template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a) { return (-a); }
template<> EIGEN_STRONG_INLINE Packet4f pnegate(const Packet4f& a)
{
Packet4f c;
c.v4f[0] = -a.v4f[0];
c.v4f[1] = -a.v4f[1];
return c;
}
template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return (-a); }
template<> EIGEN_STRONG_INLINE Packet4i pconj(const Packet4i& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet4f pconj(const Packet4f& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd<Packet4i>(pmul<Packet4i>(a, b), c); }
template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c)
{
Packet4f res;
res.v4f[0] = vec_madd(a.v4f[0], b.v4f[0], c.v4f[0]);
res.v4f[1] = vec_madd(a.v4f[1], b.v4f[1], c.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); }
template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a) { return padd<Packet4i>(pset1<Packet4i>(a), p4i_COUNTDOWN); }
template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a) { return padd<Packet4f>(pset1<Packet4f>(a), p4f_COUNTDOWN); }
template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a) { return padd<Packet2d>(pset1<Packet2d>(a), p2d_COUNTDOWN); }
template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_min(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pmin(a.v4f[0], b.v4f[0]);
res.v4f[1] = pmin(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pmax(a.v4f[0], b.v4f[0]);
res.v4f[1] = pmax(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4i pand<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4i por<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_or(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d por<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_or(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f por<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4i pxor<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_xor(a, b); }
template<> EIGEN_STRONG_INLINE Packet2d pxor<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_xor(a, b); }
template<> EIGEN_STRONG_INLINE Packet4f pxor<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return pand<Packet4i>(a, vec_nor(b, b)); }
template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, vec_nor(b, b)); }
template<> EIGEN_STRONG_INLINE Packet4f pandnot<Packet4f>(const Packet4f& a, const Packet4f& b)
{
Packet4f res;
res.v4f[0] = pandnot(a.v4f[0], b.v4f[0]);
res.v4f[1] = pandnot(a.v4f[1], b.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet4f pround<Packet4f>(const Packet4f& a)
{
Packet4f res;
res.v4f[0] = vec_round(a.v4f[0]);
res.v4f[1] = vec_round(a.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet2d pround<Packet2d>(const Packet2d& a) { return vec_round(a); }
template<> EIGEN_STRONG_INLINE Packet4f pceil<Packet4f>(const Packet4f& a)
{
Packet4f res;
res.v4f[0] = vec_ceil(a.v4f[0]);
res.v4f[1] = vec_ceil(a.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet2d pceil<Packet2d>(const Packet2d& a) { return vec_ceil(a); }
template<> EIGEN_STRONG_INLINE Packet4f pfloor<Packet4f>(const Packet4f& a)
{
Packet4f res;
res.v4f[0] = vec_floor(a.v4f[0]);
res.v4f[1] = vec_floor(a.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE Packet2d pfloor<Packet2d>(const Packet2d& a) { return vec_floor(a); }
template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from) { return pload<Packet4i>(from); }
template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from) { return pload<Packet4f>(from); }
template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from) { return pload<Packet2d>(from); }
@@ -408,6 +659,14 @@ template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int* from)
return vec_perm(p, p, p16uc_DUPLICATE32_HI);
}
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
{
Packet4f p = pload<Packet4f>(from);
p.v4f[1] = vec_splat(p.v4f[0], 1);
p.v4f[0] = vec_splat(p.v4f[0], 0);
return p;
}
template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double* from)
{
Packet2d p = pload<Packet2d>(from);
@@ -415,12 +674,15 @@ template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double* from)
}
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from) { pstore<int>(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from) { pstore<float>(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d& from) { pstore<double>(to, from); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE int pfirst<Packet4i>(const Packet4i& a) { int EIGEN_ALIGN16 x[4]; pstore(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE float pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[2]; vec_st2f(a.v4f[0], &x[0]); return x[0]; }
template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { double EIGEN_ALIGN16 x[2]; pstore(x, a); return x[0]; }
template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a)
@@ -433,8 +695,23 @@ template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a)
return reinterpret_cast<Packet2d>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE64));
}
template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vec_abs(a); }
template<> EIGEN_STRONG_INLINE Packet2d pabs(const Packet2d& a) { return vec_abs(a); }
template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a)
{
Packet4f rev;
rev.v4f[0] = preverse<Packet2d>(a.v4f[1]);
rev.v4f[1] = preverse<Packet2d>(a.v4f[0]);
return rev;
}
template<> EIGEN_STRONG_INLINE Packet4i pabs<Packet4i>(const Packet4i& a) { return vec_abs(a); }
template<> EIGEN_STRONG_INLINE Packet2d pabs<Packet2d>(const Packet2d& a) { return vec_abs(a); }
template<> EIGEN_STRONG_INLINE Packet4f pabs<Packet4f>(const Packet4f& a)
{
Packet4f res;
res.v4f[0] = pabs(a.v4f[0]);
res.v4f[1] = pabs(a.v4f[1]);
return res;
}
template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
{
@@ -453,6 +730,13 @@ template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
sum = padd<Packet2d>(a, b);
return pfirst(sum);
}
template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
{
Packet2d sum;
sum = padd<Packet2d>(a.v4f[0], a.v4f[1]);
double first = predux<Packet2d>(sum);
return static_cast<float>(first);
}
template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
{
@@ -493,6 +777,21 @@ template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
return sum;
}
template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
{
PacketBlock<Packet4f,4> transpose;
transpose.packet[0] = vecs[0];
transpose.packet[1] = vecs[1];
transpose.packet[2] = vecs[2];
transpose.packet[3] = vecs[3];
ptranspose(transpose);
Packet4f sum = padd(transpose.packet[0], transpose.packet[1]);
sum = padd(sum, transpose.packet[2]);
sum = padd(sum, transpose.packet[3]);
return sum;
}
// Other reduction functions:
// mul
template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
@@ -507,6 +806,12 @@ template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a)
return pfirst(pmul(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
}
template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
{
// Return predux_mul<Packet2d> of the subvectors product
return static_cast<float>(pfirst(predux_mul(pmul(a.v4f[0], a.v4f[1]))));
}
// min
template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
{
@@ -521,6 +826,14 @@ template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a)
return pfirst(pmin<Packet2d>(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
}
template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
{
Packet2d b, res;
b = pmin<Packet2d>(a.v4f[0], a.v4f[1]);
res = pmin<Packet2d>(b, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(b), reinterpret_cast<Packet4i>(b), 8)));
return static_cast<float>(pfirst(res));
}
// max
template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
{
@@ -536,6 +849,14 @@ template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a)
return pfirst(pmax<Packet2d>(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
}
template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
{
Packet2d b, res;
b = pmax<Packet2d>(a.v4f[0], a.v4f[1]);
res = pmax<Packet2d>(b, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(b), reinterpret_cast<Packet4i>(b), 8)));
return static_cast<float>(pfirst(res));
}
EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<Packet4i,4>& kernel) {
Packet4i t0 = vec_mergeh(kernel.packet[0], kernel.packet[2]);
@@ -556,12 +877,61 @@ ptranspose(PacketBlock<Packet2d,2>& kernel) {
kernel.packet[1] = t1;
}
/* Split the Packet4f PacketBlock into 4 Packet2d PacketBlocks and transpose each one
*/
EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<Packet4f,4>& kernel) {
PacketBlock<Packet2d,2> t0,t1,t2,t3;
// copy top-left 2x2 Packet2d block
t0.packet[0] = kernel.packet[0].v4f[0];
t0.packet[1] = kernel.packet[1].v4f[0];
// copy top-right 2x2 Packet2d block
t1.packet[0] = kernel.packet[0].v4f[1];
t1.packet[1] = kernel.packet[1].v4f[1];
// copy bottom-left 2x2 Packet2d block
t2.packet[0] = kernel.packet[2].v4f[0];
t2.packet[1] = kernel.packet[3].v4f[0];
// copy bottom-right 2x2 Packet2d block
t3.packet[0] = kernel.packet[2].v4f[1];
t3.packet[1] = kernel.packet[3].v4f[1];
// Transpose all 2x2 blocks
ptranspose(t0);
ptranspose(t1);
ptranspose(t2);
ptranspose(t3);
// Copy back transposed blocks, but exchange t1 and t2 due to transposition
kernel.packet[0].v4f[0] = t0.packet[0];
kernel.packet[0].v4f[1] = t2.packet[0];
kernel.packet[1].v4f[0] = t0.packet[1];
kernel.packet[1].v4f[1] = t2.packet[1];
kernel.packet[2].v4f[0] = t1.packet[0];
kernel.packet[2].v4f[1] = t3.packet[0];
kernel.packet[3].v4f[0] = t1.packet[1];
kernel.packet[3].v4f[1] = t3.packet[1];
}
template<> EIGEN_STRONG_INLINE Packet4i pblend(const Selector<4>& ifPacket, const Packet4i& thenPacket, const Packet4i& elsePacket) {
Packet4ui select = { ifPacket.select[0], ifPacket.select[1], ifPacket.select[2], ifPacket.select[3] };
Packet4ui mask = vec_cmpeq(select, reinterpret_cast<Packet4ui>(p4i_ONE));
return vec_sel(elsePacket, thenPacket, mask);
}
template<> EIGEN_STRONG_INLINE Packet4f pblend(const Selector<4>& ifPacket, const Packet4f& thenPacket, const Packet4f& elsePacket) {
Packet2ul select_hi = { ifPacket.select[0], ifPacket.select[1] };
Packet2ul select_lo = { ifPacket.select[2], ifPacket.select[3] };
Packet2ul mask_hi = vec_cmpeq(select_hi, reinterpret_cast<Packet2ul>(p2l_ONE));
Packet2ul mask_lo = vec_cmpeq(select_lo, reinterpret_cast<Packet2ul>(p2l_ONE));
Packet4f result;
result.v4f[0] = vec_sel(elsePacket.v4f[0], thenPacket.v4f[0], mask_hi);
result.v4f[1] = vec_sel(elsePacket.v4f[1], thenPacket.v4f[1], mask_lo);
return result;
}
template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) {
Packet2ul select = { ifPacket.select[0], ifPacket.select[1] };
Packet2ul mask = vec_cmpeq(select, reinterpret_cast<Packet2ul>(p2l_ONE));

View File

@@ -28,7 +28,7 @@ template<typename DstScalar,typename SrcScalar> struct assign_op {
{ internal::pstoret<DstScalar,Packet,Alignment>(a,b); }
};
// Empty overload for void type (used by PermutationMatrix
// Empty overload for void type (used by PermutationMatrix)
template<typename DstScalar> struct assign_op<DstScalar,void> {};
template<typename DstScalar,typename SrcScalar>

View File

@@ -255,7 +255,7 @@ struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_NEQ> : binary_op_base<LhsScalar,Rh
/** \internal
* \brief Template functor to compute the hypot of two scalars
* \brief Template functor to compute the hypot of two \b positive \b and \b real scalars
*
* \sa MatrixBase::stableNorm(), class Redux
*/
@@ -263,22 +263,15 @@ template<typename Scalar>
struct scalar_hypot_op<Scalar,Scalar> : binary_op_base<Scalar,Scalar>
{
EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
// typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar &x, const Scalar &y) const
{
EIGEN_USING_STD_MATH(sqrt)
Scalar p, qp;
if(_x>_y)
{
p = _x;
qp = _y / p;
}
else
{
p = _y;
qp = _x / p;
}
return p * sqrt(Scalar(1) + qp*qp);
// This functor is used by hypotNorm only for which it is faster to first apply abs
// on all coefficients prior to reduction through hypot.
// This way we avoid calling abs on positive and real entries, and this also permits
// to seamlessly handle complexes. Otherwise we would have to handle both real and complexes
// through the same functor...
return internal::positive_real_hypot(x,y);
}
};
template<typename Scalar>

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@@ -44,16 +44,16 @@ struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/false>
{
linspaced_op_impl(const Scalar& low, const Scalar& high, Index num_steps) :
m_low(low), m_high(high), m_size1(num_steps==1 ? 1 : num_steps-1), m_step(num_steps==1 ? Scalar() : (high-low)/Scalar(num_steps-1)),
m_interPacket(plset<Packet>(0)),
m_flip(std::abs(high)<std::abs(low))
m_flip(numext::abs(high)<numext::abs(low))
{}
template<typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (IndexType i) const {
typedef typename NumTraits<Scalar>::Real RealScalar;
if(m_flip)
return (i==0)? m_low : (m_high - (m_size1-i)*m_step);
return (i==0)? m_low : (m_high - RealScalar(m_size1-i)*m_step);
else
return (i==m_size1)? m_high : (m_low + i*m_step);
return (i==m_size1)? m_high : (m_low + RealScalar(i)*m_step);
}
template<typename IndexType>
@@ -63,7 +63,7 @@ struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/false>
// [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
if(m_flip)
{
Packet pi = padd(pset1<Packet>(Scalar(i-m_size1)),m_interPacket);
Packet pi = plset<Packet>(Scalar(i-m_size1));
Packet res = padd(pset1<Packet>(m_high), pmul(pset1<Packet>(m_step), pi));
if(i==0)
res = pinsertfirst(res, m_low);
@@ -71,7 +71,7 @@ struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/false>
}
else
{
Packet pi = padd(pset1<Packet>(Scalar(i)),m_interPacket);
Packet pi = plset<Packet>(Scalar(i));
Packet res = padd(pset1<Packet>(m_low), pmul(pset1<Packet>(m_step), pi));
if(i==m_size1-unpacket_traits<Packet>::size+1)
res = pinsertlast(res, m_high);
@@ -83,7 +83,6 @@ struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/false>
const Scalar m_high;
const Index m_size1;
const Scalar m_step;
const Packet m_interPacket;
const bool m_flip;
};
@@ -93,8 +92,8 @@ struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/true>
linspaced_op_impl(const Scalar& low, const Scalar& high, Index num_steps) :
m_low(low),
m_multiplier((high-low)/convert_index<Scalar>(num_steps<=1 ? 1 : num_steps-1)),
m_divisor(convert_index<Scalar>(num_steps+high-low)/(high-low+1)),
m_use_divisor((high-low+1)<num_steps)
m_divisor(convert_index<Scalar>((high>=low?num_steps:-num_steps)+(high-low))/((numext::abs(high-low)+1)==0?1:(numext::abs(high-low)+1))),
m_use_divisor(num_steps>1 && (numext::abs(high-low)+1)<num_steps)
{}
template<typename IndexType>
@@ -173,6 +172,13 @@ template<typename Scalar, typename PacketType,typename IndexType>
struct has_unary_operator<linspaced_op<Scalar,PacketType>,IndexType> { enum { value = 1}; };
template<typename Scalar, typename PacketType,typename IndexType>
struct has_binary_operator<linspaced_op<Scalar,PacketType>,IndexType> { enum { value = 0}; };
template<typename Scalar,typename IndexType>
struct has_nullary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 1}; };
template<typename Scalar,typename IndexType>
struct has_unary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 0}; };
template<typename Scalar,typename IndexType>
struct has_binary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 0}; };
#endif
} // end namespace internal

View File

@@ -72,7 +72,7 @@ template<typename T>
struct functor_traits<std::not_equal_to<T> >
{ enum { Cost = 1, PacketAccess = false }; };
#if(__cplusplus < 201103L)
#if (__cplusplus < 201103L) && (EIGEN_COMP_MSVC <= 1900)
// std::binder* are deprecated since c++11 and will be removed in c++17
template<typename T>
struct functor_traits<std::binder2nd<T> >
@@ -83,13 +83,17 @@ struct functor_traits<std::binder1st<T> >
{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
#endif
#if (__cplusplus < 201703L) && (EIGEN_COMP_MSVC < 1910)
// std::unary_negate is deprecated since c++17 and will be removed in c++20
template<typename T>
struct functor_traits<std::unary_negate<T> >
{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
// std::binary_negate is deprecated since c++17 and will be removed in c++20
template<typename T>
struct functor_traits<std::binary_negate<T> >
{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
#endif
#ifdef EIGEN_STDEXT_SUPPORT

View File

@@ -972,7 +972,7 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
EIGEN_ASM_COMMENT("begin step of gebp micro kernel 3pX4"); \
EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
internal::prefetch(blA+(3*K+16)*LhsProgress); \
if (EIGEN_ARCH_ARM) internal::prefetch(blB+(4*K+16)*RhsProgress); /* Bug 953 */ \
if (EIGEN_ARCH_ARM) { internal::prefetch(blB+(4*K+16)*RhsProgress); } /* Bug 953 */ \
traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0); \
traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1); \
traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2); \
@@ -1197,10 +1197,16 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
EIGEN_ASM_COMMENT("begin gebp micro kernel 2pX4");
RhsPacket B_0, B1, B2, B3, T0;
#define EIGEN_GEBGP_ONESTEP(K) \
// NOTE: the begin/end asm comments below work around bug 935!
// but they are not enough for gcc>=6 without FMA (bug 1637)
#if EIGEN_GNUC_AT_LEAST(6,0)
#define EIGEN_GEBP_2PX4_SPILLING_WORKAROUND __asm__ ("" : [a0] "+rm" (A0),[a1] "+rm" (A1));
#else
#define EIGEN_GEBP_2PX4_SPILLING_WORKAROUND
#endif
#define EIGEN_GEBGP_ONESTEP(K) \
do { \
EIGEN_ASM_COMMENT("begin step of gebp micro kernel 2pX4"); \
EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
traits.loadLhs(&blA[(0+2*K)*LhsProgress], A0); \
traits.loadLhs(&blA[(1+2*K)*LhsProgress], A1); \
traits.broadcastRhs(&blB[(0+4*K)*RhsProgress], B_0, B1, B2, B3); \
@@ -1212,6 +1218,7 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
traits.madd(A1, B2, C6, B2); \
traits.madd(A0, B3, C3, T0); \
traits.madd(A1, B3, C7, B3); \
EIGEN_GEBP_2PX4_SPILLING_WORKAROUND \
EIGEN_ASM_COMMENT("end step of gebp micro kernel 2pX4"); \
} while(false)
@@ -1526,10 +1533,10 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
// The following piece of code wont work for 512 bit registers
// Moreover, if LhsProgress==8 it assumes that there is a half packet of the same size
// as nr (which is currently 4) for the return type.
typedef typename unpacket_traits<SResPacket>::half SResPacketHalf;
const int SResPacketHalfSize = unpacket_traits<typename unpacket_traits<SResPacket>::half>::size;
if ((SwappedTraits::LhsProgress % 4) == 0 &&
(SwappedTraits::LhsProgress <= 8) &&
(SwappedTraits::LhsProgress!=8 || unpacket_traits<SResPacketHalf>::size==nr))
(SwappedTraits::LhsProgress!=8 || SResPacketHalfSize==nr))
{
SAccPacket C0, C1, C2, C3;
straits.initAcc(C0);

View File

@@ -83,8 +83,8 @@ static void run(Index rows, Index cols, Index depth,
if(info)
{
// this is the parallel version!
Index tid = omp_get_thread_num();
Index threads = omp_get_num_threads();
int tid = omp_get_thread_num();
int threads = omp_get_num_threads();
LhsScalar* blockA = blocking.blockA();
eigen_internal_assert(blockA!=0);
@@ -116,9 +116,9 @@ static void run(Index rows, Index cols, Index depth,
info[tid].sync = k;
// Computes C_i += A' * B' per A'_i
for(Index shift=0; shift<threads; ++shift)
for(int shift=0; shift<threads; ++shift)
{
Index i = (tid+shift)%threads;
int i = (tid+shift)%threads;
// At this point we have to make sure that A'_i has been updated by the thread i,
// we use testAndSetOrdered to mimic a volatile access.

View File

@@ -148,7 +148,7 @@ struct tribb_kernel
ResMapper res(_res, resStride);
gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, mr, nr, ConjLhs, ConjRhs> gebp_kernel;
Matrix<ResScalar,BlockSize,BlockSize,ColMajor> buffer;
Matrix<ResScalar,BlockSize,BlockSize,ColMajor> buffer((internal::constructor_without_unaligned_array_assert()));
// let's process the block per panel of actual_mc x BlockSize,
// again, each is split into three parts, etc.
@@ -199,7 +199,7 @@ struct general_product_to_triangular_selector;
template<typename MatrixType, typename ProductType, int UpLo>
struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
{
static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha)
static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha, bool beta)
{
typedef typename MatrixType::Scalar Scalar;
@@ -217,6 +217,9 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
if(!beta)
mat.template triangularView<UpLo>().setZero();
enum {
StorageOrder = (internal::traits<MatrixType>::Flags&RowMajorBit) ? RowMajor : ColMajor,
UseLhsDirectly = _ActualLhs::InnerStrideAtCompileTime==1,
@@ -244,7 +247,7 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
template<typename MatrixType, typename ProductType, int UpLo>
struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
{
static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha)
static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha, bool beta)
{
typedef typename internal::remove_all<typename ProductType::LhsNested>::type Lhs;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
@@ -260,13 +263,19 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
typename ProductType::Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
if(!beta)
mat.template triangularView<UpLo>().setZero();
enum {
IsRowMajor = (internal::traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0,
LhsIsRowMajor = _ActualLhs::Flags&RowMajorBit ? 1 : 0,
RhsIsRowMajor = _ActualRhs::Flags&RowMajorBit ? 1 : 0
RhsIsRowMajor = _ActualRhs::Flags&RowMajorBit ? 1 : 0,
SkipDiag = (UpLo&(UnitDiag|ZeroDiag))!=0
};
Index size = mat.cols();
if(SkipDiag)
size--;
Index depth = actualLhs.cols();
typedef internal::gemm_blocking_space<IsRowMajor ? RowMajor : ColMajor,typename Lhs::Scalar,typename Rhs::Scalar,
@@ -277,20 +286,22 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
internal::general_matrix_matrix_triangular_product<Index,
typename Lhs::Scalar, LhsIsRowMajor ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
typename Rhs::Scalar, RhsIsRowMajor ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
IsRowMajor ? RowMajor : ColMajor, UpLo>
IsRowMajor ? RowMajor : ColMajor, UpLo&(Lower|Upper)>
::run(size, depth,
&actualLhs.coeffRef(0,0), actualLhs.outerStride(), &actualRhs.coeffRef(0,0), actualRhs.outerStride(),
mat.data(), mat.outerStride(), actualAlpha, blocking);
&actualLhs.coeffRef(SkipDiag&&(UpLo&Lower)==Lower ? 1 : 0,0), actualLhs.outerStride(),
&actualRhs.coeffRef(0,SkipDiag&&(UpLo&Upper)==Upper ? 1 : 0), actualRhs.outerStride(),
mat.data() + (SkipDiag ? (bool(IsRowMajor) != ((UpLo&Lower)==Lower) ? 1 : mat.outerStride() ) : 0), mat.outerStride(), actualAlpha, blocking);
}
};
template<typename MatrixType, unsigned int UpLo>
template<typename ProductType>
TriangularView<MatrixType,UpLo>& TriangularViewImpl<MatrixType,UpLo,Dense>::_assignProduct(const ProductType& prod, const Scalar& alpha)
TriangularView<MatrixType,UpLo>& TriangularViewImpl<MatrixType,UpLo,Dense>::_assignProduct(const ProductType& prod, const Scalar& alpha, bool beta)
{
EIGEN_STATIC_ASSERT((UpLo&UnitDiag)==0, WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED);
eigen_assert(derived().nestedExpression().rows() == prod.rows() && derived().cols() == prod.cols());
general_product_to_triangular_selector<MatrixType, ProductType, UpLo, internal::traits<ProductType>::InnerSize==1>::run(derived().nestedExpression().const_cast_derived(), prod, alpha);
general_product_to_triangular_selector<MatrixType, ProductType, UpLo, internal::traits<ProductType>::InnerSize==1>::run(derived().nestedExpression().const_cast_derived(), prod, alpha, beta);
return derived();
}

View File

@@ -33,7 +33,7 @@
#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_BLAS_H
#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_BLAS_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -52,7 +52,7 @@ struct general_matrix_matrix_triangular_product<Index,Scalar,LhsStorageOrder,Con
static EIGEN_STRONG_INLINE void run(Index size, Index depth,const Scalar* lhs, Index lhsStride, \
const Scalar* rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar, Scalar>& blocking) \
{ \
if (lhs==rhs) { \
if ( lhs==rhs && ((UpLo&(Lower|Upper))==UpLo) ) { \
general_matrix_matrix_rankupdate<Index,Scalar,LhsStorageOrder,ConjugateLhs,ColMajor,UpLo> \
::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha,blocking); \
} else { \
@@ -86,9 +86,9 @@ struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,C
/* typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs;*/ \
\
BlasIndex lda=convert_index<BlasIndex>(lhsStride), ldc=convert_index<BlasIndex>(resStride), n=convert_index<BlasIndex>(size), k=convert_index<BlasIndex>(depth); \
char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'T':'N'; \
EIGTYPE beta; \
BLASFUNC(&uplo, &trans, &n, &k, &numext::real_ref(alpha), lhs, &lda, &numext::real_ref(beta), res, &ldc); \
char uplo=((IsLower) ? 'L' : 'U'), trans=((AStorageOrder==RowMajor) ? 'T':'N'); \
EIGTYPE beta(1); \
BLASFUNC(&uplo, &trans, &n, &k, (const BLASTYPE*)&numext::real_ref(alpha), lhs, &lda, (const BLASTYPE*)&numext::real_ref(beta), res, &ldc); \
} \
};
@@ -107,7 +107,7 @@ struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,C
typedef Matrix<EIGTYPE, Dynamic, Dynamic, AStorageOrder> MatrixType; \
\
BlasIndex lda=convert_index<BlasIndex>(lhsStride), ldc=convert_index<BlasIndex>(resStride), n=convert_index<BlasIndex>(size), k=convert_index<BlasIndex>(depth); \
char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'C':'N'; \
char uplo=((IsLower) ? 'L' : 'U'), trans=((AStorageOrder==RowMajor) ? 'C':'N'); \
RTYPE alpha_, beta_; \
const EIGTYPE* a_ptr; \
\
@@ -125,9 +125,13 @@ struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,C
} \
};
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_RANKUPDATE_R(double, double, dsyrk)
EIGEN_BLAS_RANKUPDATE_R(float, float, ssyrk)
#else
EIGEN_BLAS_RANKUPDATE_R(double, double, dsyrk_)
EIGEN_BLAS_RANKUPDATE_R(float, float, ssyrk_)
#endif
// TODO hanlde complex cases
// EIGEN_BLAS_RANKUPDATE_C(dcomplex, double, double, zherk_)

View File

@@ -46,7 +46,7 @@ namespace internal {
// gemm specialization
#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, BLASTYPE, BLASPREFIX) \
#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, BLASTYPE, BLASFUNC) \
template< \
typename Index, \
int LhsStorageOrder, bool ConjugateLhs, \
@@ -100,13 +100,20 @@ static void run(Index rows, Index cols, Index depth, \
ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
} else b = _rhs; \
\
BLASPREFIX##gemm_(&transa, &transb, &m, &n, &k, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
BLASFUNC(&transa, &transb, &m, &n, &k, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
}};
GEMM_SPECIALIZATION(double, d, double, d)
GEMM_SPECIALIZATION(float, f, float, s)
GEMM_SPECIALIZATION(dcomplex, cd, double, z)
GEMM_SPECIALIZATION(scomplex, cf, float, c)
#ifdef EIGEN_USE_MKL
GEMM_SPECIALIZATION(double, d, double, dgemm)
GEMM_SPECIALIZATION(float, f, float, sgemm)
GEMM_SPECIALIZATION(dcomplex, cd, MKL_Complex16, zgemm)
GEMM_SPECIALIZATION(scomplex, cf, MKL_Complex8, cgemm)
#else
GEMM_SPECIALIZATION(double, d, double, dgemm_)
GEMM_SPECIALIZATION(float, f, float, sgemm_)
GEMM_SPECIALIZATION(dcomplex, cd, double, zgemm_)
GEMM_SPECIALIZATION(scomplex, cf, float, cgemm_)
#endif
} // end namespase internal

View File

@@ -183,8 +183,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,C
alignmentPattern = AllAligned;
}
const Index offset1 = (FirstAligned && alignmentStep==1)?3:1;
const Index offset3 = (FirstAligned && alignmentStep==1)?1:3;
const Index offset1 = (alignmentPattern==FirstAligned && alignmentStep==1)?3:1;
const Index offset3 = (alignmentPattern==FirstAligned && alignmentStep==1)?1:3;
Index columnBound = ((cols-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
for (Index i=skipColumns; i<columnBound; i+=columnsAtOnce)
@@ -457,8 +457,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,R
alignmentPattern = AllAligned;
}
const Index offset1 = (FirstAligned && alignmentStep==1)?3:1;
const Index offset3 = (FirstAligned && alignmentStep==1)?1:3;
const Index offset1 = (alignmentPattern==FirstAligned && alignmentStep==1)?3:1;
const Index offset3 = (alignmentPattern==FirstAligned && alignmentStep==1)?1:3;
Index rowBound = ((rows-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
for (Index i=skipRows; i<rowBound; i+=rowsAtOnce)

View File

@@ -85,7 +85,7 @@ EIGEN_BLAS_GEMV_SPECIALIZE(float)
EIGEN_BLAS_GEMV_SPECIALIZE(dcomplex)
EIGEN_BLAS_GEMV_SPECIALIZE(scomplex)
#define EIGEN_BLAS_GEMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASPREFIX) \
#define EIGEN_BLAS_GEMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASFUNC) \
template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \
struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \
{ \
@@ -113,14 +113,21 @@ static void run( \
x_ptr=x_tmp.data(); \
incx=1; \
} else x_ptr=rhs; \
BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \
BLASFUNC(&trans, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &incy); \
}\
};
EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, d)
EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, s)
EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, double, z)
EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, float, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, dgemv)
EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, sgemv)
EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, zgemv)
EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, MKL_Complex8 , cgemv)
#else
EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, dgemv_)
EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, sgemv_)
EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, double, zgemv_)
EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, float, cgemv_)
#endif
} // end namespase internal

View File

@@ -75,7 +75,7 @@ template<typename Index> struct GemmParallelInfo
{
GemmParallelInfo() : sync(-1), users(0), lhs_start(0), lhs_length(0) {}
int volatile sync;
Index volatile sync;
int volatile users;
Index lhs_start;
@@ -104,13 +104,14 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, Index depth,
// - the sizes are large enough
// compute the maximal number of threads from the size of the product:
// FIXME this has to be fine tuned
// This first heuristic takes into account that the product kernel is fully optimized when working with nr columns at once.
Index size = transpose ? rows : cols;
Index pb_max_threads = std::max<Index>(1,size / 32);
Index pb_max_threads = std::max<Index>(1,size / Functor::Traits::nr);
// compute the maximal number of threads from the total amount of work:
double work = static_cast<double>(rows) * static_cast<double>(cols) *
static_cast<double>(depth);
double kMinTaskSize = 50000; // Heuristic.
double kMinTaskSize = 50000; // FIXME improve this heuristic.
pb_max_threads = std::max<Index>(1, std::min<Index>(pb_max_threads, work / kMinTaskSize));
// compute the number of threads we are going to use

View File

@@ -40,7 +40,7 @@ namespace internal {
/* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */
#define EIGEN_BLAS_SYMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_SYMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -81,13 +81,13 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLh
ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
} else b = _rhs; \
\
BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
\
} \
};
#define EIGEN_BLAS_HEMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_HEMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -144,20 +144,26 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLh
ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
} \
\
BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
\
} \
};
EIGEN_BLAS_SYMM_L(double, double, d, d)
EIGEN_BLAS_SYMM_L(float, float, f, s)
EIGEN_BLAS_HEMM_L(dcomplex, double, cd, z)
EIGEN_BLAS_HEMM_L(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_SYMM_L(double, double, d, dsymm)
EIGEN_BLAS_SYMM_L(float, float, f, ssymm)
EIGEN_BLAS_HEMM_L(dcomplex, MKL_Complex16, cd, zhemm)
EIGEN_BLAS_HEMM_L(scomplex, MKL_Complex8, cf, chemm)
#else
EIGEN_BLAS_SYMM_L(double, double, d, dsymm_)
EIGEN_BLAS_SYMM_L(float, float, f, ssymm_)
EIGEN_BLAS_HEMM_L(dcomplex, double, cd, zhemm_)
EIGEN_BLAS_HEMM_L(scomplex, float, cf, chemm_)
#endif
/* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */
#define EIGEN_BLAS_SYMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_SYMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -197,13 +203,13 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateL
ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
} else b = _lhs; \
\
BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
\
} \
};
#define EIGEN_BLAS_HEMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_HEMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -259,15 +265,21 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateL
ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
} \
\
BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
} \
};
EIGEN_BLAS_SYMM_R(double, double, d, d)
EIGEN_BLAS_SYMM_R(float, float, f, s)
EIGEN_BLAS_HEMM_R(dcomplex, double, cd, z)
EIGEN_BLAS_HEMM_R(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_SYMM_R(double, double, d, dsymm)
EIGEN_BLAS_SYMM_R(float, float, f, ssymm)
EIGEN_BLAS_HEMM_R(dcomplex, MKL_Complex16, cd, zhemm)
EIGEN_BLAS_HEMM_R(scomplex, MKL_Complex8, cf, chemm)
#else
EIGEN_BLAS_SYMM_R(double, double, d, dsymm_)
EIGEN_BLAS_SYMM_R(float, float, f, ssymm_)
EIGEN_BLAS_HEMM_R(dcomplex, double, cd, zhemm_)
EIGEN_BLAS_HEMM_R(scomplex, float, cf, chemm_)
#endif
} // end namespace internal
} // end namespace Eigen

View File

@@ -83,10 +83,10 @@ EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrd
Scalar t3(0);
Packet ptmp3 = pset1<Packet>(t3);
size_t starti = FirstTriangular ? 0 : j+2;
size_t endi = FirstTriangular ? j : size;
size_t alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti);
size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
Index starti = FirstTriangular ? 0 : j+2;
Index endi = FirstTriangular ? j : size;
Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti);
Index alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
res[j] += cjd.pmul(numext::real(A0[j]), t0);
res[j+1] += cjd.pmul(numext::real(A1[j+1]), t1);
@@ -101,7 +101,7 @@ EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrd
t2 += cj1.pmul(A0[j+1], rhs[j+1]);
}
for (size_t i=starti; i<alignedStart; ++i)
for (Index i=starti; i<alignedStart; ++i)
{
res[i] += cj0.pmul(A0[i], t0) + cj0.pmul(A1[i],t1);
t2 += cj1.pmul(A0[i], rhs[i]);
@@ -113,7 +113,7 @@ EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrd
const Scalar* EIGEN_RESTRICT a1It = A1 + alignedStart;
const Scalar* EIGEN_RESTRICT rhsIt = rhs + alignedStart;
Scalar* EIGEN_RESTRICT resIt = res + alignedStart;
for (size_t i=alignedStart; i<alignedEnd; i+=PacketSize)
for (Index i=alignedStart; i<alignedEnd; i+=PacketSize)
{
Packet A0i = ploadu<Packet>(a0It); a0It += PacketSize;
Packet A1i = ploadu<Packet>(a1It); a1It += PacketSize;
@@ -125,7 +125,7 @@ EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrd
ptmp3 = pcj1.pmadd(A1i, Bi, ptmp3);
pstore(resIt,Xi); resIt += PacketSize;
}
for (size_t i=alignedEnd; i<endi; i++)
for (Index i=alignedEnd; i<endi; i++)
{
res[i] += cj0.pmul(A0[i], t0) + cj0.pmul(A1[i],t1);
t2 += cj1.pmul(A0[i], rhs[i]);

View File

@@ -95,14 +95,21 @@ const EIGTYPE* _rhs, EIGTYPE* res, EIGTYPE alpha) \
x_tmp=map_x.conjugate(); \
x_ptr=x_tmp.data(); \
} else x_ptr=_rhs; \
BLASFUNC(&uplo, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \
BLASFUNC(&uplo, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &incy); \
}\
};
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_SYMV_SPECIALIZATION(double, double, dsymv)
EIGEN_BLAS_SYMV_SPECIALIZATION(float, float, ssymv)
EIGEN_BLAS_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv)
EIGEN_BLAS_SYMV_SPECIALIZATION(scomplex, MKL_Complex8, chemv)
#else
EIGEN_BLAS_SYMV_SPECIALIZATION(double, double, dsymv_)
EIGEN_BLAS_SYMV_SPECIALIZATION(float, float, ssymv_)
EIGEN_BLAS_SYMV_SPECIALIZATION(dcomplex, double, zhemv_)
EIGEN_BLAS_SYMV_SPECIALIZATION(scomplex, float, chemv_)
#endif
} // end namespace internal

View File

@@ -137,7 +137,13 @@ EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,true,
ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer;
// To work around an "error: member reference base type 'Matrix<...>
// (Eigen::internal::constructor_without_unaligned_array_assert (*)())' is
// not a structure or union" compilation error in nvcc (tested V8.0.61),
// create a dummy internal::constructor_without_unaligned_array_assert
// object to pass to the Matrix constructor.
internal::constructor_without_unaligned_array_assert a;
Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer(a);
triangularBuffer.setZero();
if((Mode&ZeroDiag)==ZeroDiag)
triangularBuffer.diagonal().setZero();
@@ -284,7 +290,8 @@ EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,false,
ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer;
internal::constructor_without_unaligned_array_assert a;
Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer(a);
triangularBuffer.setZero();
if((Mode&ZeroDiag)==ZeroDiag)
triangularBuffer.diagonal().setZero();
@@ -393,7 +400,9 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
{
template<typename Dest> static void run(Dest& dst, const Lhs &a_lhs, const Rhs &a_rhs, const typename Dest::Scalar& alpha)
{
typedef typename Dest::Scalar Scalar;
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
typedef typename Dest::Scalar Scalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
@@ -405,8 +414,9 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
* RhsBlasTraits::extractScalarFactor(a_rhs);
LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(a_lhs);
RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(a_rhs);
Scalar actualAlpha = alpha * lhs_alpha * rhs_alpha;
typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,4> BlockingType;
@@ -431,6 +441,21 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
&dst.coeffRef(0,0), dst.outerStride(), // result info
actualAlpha, blocking
);
// Apply correction if the diagonal is unit and a scalar factor was nested:
if ((Mode&UnitDiag)==UnitDiag)
{
if (LhsIsTriangular && lhs_alpha!=LhsScalar(1))
{
Index diagSize = (std::min)(lhs.rows(),lhs.cols());
dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize);
}
else if ((!LhsIsTriangular) && rhs_alpha!=RhsScalar(1))
{
Index diagSize = (std::min)(rhs.rows(),rhs.cols());
dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
}
}
}
};

View File

@@ -75,7 +75,7 @@ EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, true)
EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, false)
// implements col-major += alpha * op(triangular) * op(general)
#define EIGEN_BLAS_TRMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_TRMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, int Mode, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -172,7 +172,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
} \
/*std::cout << "TRMM_L: A is square! Go to BLAS TRMM implementation! \n";*/ \
/* call ?trmm*/ \
BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
\
/* Add op(a_triangular)*b into res*/ \
Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
@@ -180,13 +180,20 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
} \
};
EIGEN_BLAS_TRMM_L(double, double, d, d)
EIGEN_BLAS_TRMM_L(dcomplex, double, cd, z)
EIGEN_BLAS_TRMM_L(float, float, f, s)
EIGEN_BLAS_TRMM_L(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRMM_L(double, double, d, dtrmm)
EIGEN_BLAS_TRMM_L(dcomplex, MKL_Complex16, cd, ztrmm)
EIGEN_BLAS_TRMM_L(float, float, f, strmm)
EIGEN_BLAS_TRMM_L(scomplex, MKL_Complex8, cf, ctrmm)
#else
EIGEN_BLAS_TRMM_L(double, double, d, dtrmm_)
EIGEN_BLAS_TRMM_L(dcomplex, double, cd, ztrmm_)
EIGEN_BLAS_TRMM_L(float, float, f, strmm_)
EIGEN_BLAS_TRMM_L(scomplex, float, cf, ctrmm_)
#endif
// implements col-major += alpha * op(general) * op(triangular)
#define EIGEN_BLAS_TRMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_TRMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \
template <typename Index, int Mode, \
int LhsStorageOrder, bool ConjugateLhs, \
int RhsStorageOrder, bool ConjugateRhs> \
@@ -282,7 +289,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
} \
/*std::cout << "TRMM_R: A is square! Go to BLAS TRMM implementation! \n";*/ \
/* call ?trmm*/ \
BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
\
/* Add op(a_triangular)*b into res*/ \
Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
@@ -290,11 +297,17 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
} \
};
EIGEN_BLAS_TRMM_R(double, double, d, d)
EIGEN_BLAS_TRMM_R(dcomplex, double, cd, z)
EIGEN_BLAS_TRMM_R(float, float, f, s)
EIGEN_BLAS_TRMM_R(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRMM_R(double, double, d, dtrmm)
EIGEN_BLAS_TRMM_R(dcomplex, MKL_Complex16, cd, ztrmm)
EIGEN_BLAS_TRMM_R(float, float, f, strmm)
EIGEN_BLAS_TRMM_R(scomplex, MKL_Complex8, cf, ctrmm)
#else
EIGEN_BLAS_TRMM_R(double, double, d, dtrmm_)
EIGEN_BLAS_TRMM_R(dcomplex, double, cd, ztrmm_)
EIGEN_BLAS_TRMM_R(float, float, f, strmm_)
EIGEN_BLAS_TRMM_R(scomplex, float, cf, ctrmm_)
#endif
} // end namespace internal
} // end namespace Eigen

View File

@@ -221,8 +221,9 @@ template<int Mode> struct trmv_selector<Mode,ColMajor>
typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(rhs);
LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(lhs);
RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(rhs);
ResScalar actualAlpha = alpha * lhs_alpha * rhs_alpha;
enum {
// FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
@@ -274,6 +275,12 @@ template<int Mode> struct trmv_selector<Mode,ColMajor>
else
dest = MappedDest(actualDestPtr, dest.size());
}
if ( ((Mode&UnitDiag)==UnitDiag) && (lhs_alpha!=LhsScalar(1)) )
{
Index diagSize = (std::min)(lhs.rows(),lhs.cols());
dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize);
}
}
};
@@ -295,8 +302,9 @@ template<int Mode> struct trmv_selector<Mode,RowMajor>
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(rhs);
LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(lhs);
RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(rhs);
ResScalar actualAlpha = alpha * lhs_alpha * rhs_alpha;
enum {
DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
@@ -326,6 +334,12 @@ template<int Mode> struct trmv_selector<Mode,RowMajor>
actualRhsPtr,1,
dest.data(),dest.innerStride(),
actualAlpha);
if ( ((Mode&UnitDiag)==UnitDiag) && (lhs_alpha!=LhsScalar(1)) )
{
Index diagSize = (std::min)(lhs.rows(),lhs.cols());
dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize);
}
}
};

View File

@@ -71,7 +71,7 @@ EIGEN_BLAS_TRMV_SPECIALIZE(dcomplex)
EIGEN_BLAS_TRMV_SPECIALIZE(scomplex)
// implements col-major: res += alpha * op(triangular) * vector
#define EIGEN_BLAS_TRMV_CM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_TRMV_CM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX, BLASPOSTFIX) \
template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
enum { \
@@ -121,10 +121,10 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
diag = IsUnitDiag ? 'U' : 'N'; \
\
/* call ?TRMV*/ \
BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
BLASPREFIX##trmv##BLASPOSTFIX(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
\
/* Add op(a_tr)rhs into res*/ \
BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
BLASPREFIX##axpy##BLASPOSTFIX(&n, (const BLASTYPE*)&numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
/* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \
if (size<(std::max)(rows,cols)) { \
if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
@@ -142,18 +142,25 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
m = convert_index<BlasIndex>(size); \
n = convert_index<BlasIndex>(cols-size); \
} \
BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \
BLASPREFIX##gemv##BLASPOSTFIX(&trans, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)y, &incy); \
} \
} \
};
EIGEN_BLAS_TRMV_CM(double, double, d, d)
EIGEN_BLAS_TRMV_CM(dcomplex, double, cd, z)
EIGEN_BLAS_TRMV_CM(float, float, f, s)
EIGEN_BLAS_TRMV_CM(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRMV_CM(double, double, d, d,)
EIGEN_BLAS_TRMV_CM(dcomplex, MKL_Complex16, cd, z,)
EIGEN_BLAS_TRMV_CM(float, float, f, s,)
EIGEN_BLAS_TRMV_CM(scomplex, MKL_Complex8, cf, c,)
#else
EIGEN_BLAS_TRMV_CM(double, double, d, d, _)
EIGEN_BLAS_TRMV_CM(dcomplex, double, cd, z, _)
EIGEN_BLAS_TRMV_CM(float, float, f, s, _)
EIGEN_BLAS_TRMV_CM(scomplex, float, cf, c, _)
#endif
// implements row-major: res += alpha * op(triangular) * vector
#define EIGEN_BLAS_TRMV_RM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
#define EIGEN_BLAS_TRMV_RM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX, BLASPOSTFIX) \
template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
enum { \
@@ -203,10 +210,10 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
diag = IsUnitDiag ? 'U' : 'N'; \
\
/* call ?TRMV*/ \
BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
BLASPREFIX##trmv##BLASPOSTFIX(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
\
/* Add op(a_tr)rhs into res*/ \
BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
BLASPREFIX##axpy##BLASPOSTFIX(&n, (const BLASTYPE*)&numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
/* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \
if (size<(std::max)(rows,cols)) { \
if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
@@ -224,15 +231,22 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
m = convert_index<BlasIndex>(size); \
n = convert_index<BlasIndex>(cols-size); \
} \
BLASPREFIX##gemv_(&trans, &n, &m, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \
BLASPREFIX##gemv##BLASPOSTFIX(&trans, &n, &m, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)y, &incy); \
} \
} \
};
EIGEN_BLAS_TRMV_RM(double, double, d, d)
EIGEN_BLAS_TRMV_RM(dcomplex, double, cd, z)
EIGEN_BLAS_TRMV_RM(float, float, f, s)
EIGEN_BLAS_TRMV_RM(scomplex, float, cf, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRMV_RM(double, double, d, d,)
EIGEN_BLAS_TRMV_RM(dcomplex, MKL_Complex16, cd, z,)
EIGEN_BLAS_TRMV_RM(float, float, f, s,)
EIGEN_BLAS_TRMV_RM(scomplex, MKL_Complex8, cf, c,)
#else
EIGEN_BLAS_TRMV_RM(double, double, d, d,_)
EIGEN_BLAS_TRMV_RM(dcomplex, double, cd, z,_)
EIGEN_BLAS_TRMV_RM(float, float, f, s,_)
EIGEN_BLAS_TRMV_RM(scomplex, float, cf, c,_)
#endif
} // end namespase internal

View File

@@ -183,7 +183,7 @@ EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conju
}
}
/* Optimized triangular solver with multiple left hand sides and the trinagular matrix on the right
/* Optimized triangular solver with multiple left hand sides and the triangular matrix on the right
*/
template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
@@ -202,6 +202,7 @@ EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conj
level3_blocking<Scalar,Scalar>& blocking)
{
Index rows = otherSize;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef blas_data_mapper<Scalar, Index, ColMajor> LhsMapper;
typedef const_blas_data_mapper<Scalar, Index, TriStorageOrder> RhsMapper;
@@ -306,9 +307,9 @@ EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conj
}
if((Mode & UnitDiag)==0)
{
Scalar b = conj(rhs(j,j));
Scalar inv_rjj = RealScalar(1)/conj(rhs(j,j));
for (Index i=0; i<actual_mc; ++i)
r[i] /= b;
r[i] *= inv_rjj;
}
}

View File

@@ -38,7 +38,7 @@ namespace Eigen {
namespace internal {
// implements LeftSide op(triangular)^-1 * general
#define EIGEN_BLAS_TRSM_L(EIGTYPE, BLASTYPE, BLASPREFIX) \
#define EIGEN_BLAS_TRSM_L(EIGTYPE, BLASTYPE, BLASFUNC) \
template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \
{ \
@@ -80,18 +80,24 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorage
} \
if (IsUnitDiag) diag='U'; \
/* call ?trsm*/ \
BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
} \
};
EIGEN_BLAS_TRSM_L(double, double, d)
EIGEN_BLAS_TRSM_L(dcomplex, double, z)
EIGEN_BLAS_TRSM_L(float, float, s)
EIGEN_BLAS_TRSM_L(scomplex, float, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRSM_L(double, double, dtrsm)
EIGEN_BLAS_TRSM_L(dcomplex, MKL_Complex16, ztrsm)
EIGEN_BLAS_TRSM_L(float, float, strsm)
EIGEN_BLAS_TRSM_L(scomplex, MKL_Complex8, ctrsm)
#else
EIGEN_BLAS_TRSM_L(double, double, dtrsm_)
EIGEN_BLAS_TRSM_L(dcomplex, double, ztrsm_)
EIGEN_BLAS_TRSM_L(float, float, strsm_)
EIGEN_BLAS_TRSM_L(scomplex, float, ctrsm_)
#endif
// implements RightSide general * op(triangular)^-1
#define EIGEN_BLAS_TRSM_R(EIGTYPE, BLASTYPE, BLASPREFIX) \
#define EIGEN_BLAS_TRSM_R(EIGTYPE, BLASTYPE, BLASFUNC) \
template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \
{ \
@@ -133,16 +139,22 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorag
} \
if (IsUnitDiag) diag='U'; \
/* call ?trsm*/ \
BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
/*std::cout << "TRMS_L specialization!\n";*/ \
} \
};
EIGEN_BLAS_TRSM_R(double, double, d)
EIGEN_BLAS_TRSM_R(dcomplex, double, z)
EIGEN_BLAS_TRSM_R(float, float, s)
EIGEN_BLAS_TRSM_R(scomplex, float, c)
#ifdef EIGEN_USE_MKL
EIGEN_BLAS_TRSM_R(double, double, dtrsm)
EIGEN_BLAS_TRSM_R(dcomplex, MKL_Complex16, ztrsm)
EIGEN_BLAS_TRSM_R(float, float, strsm)
EIGEN_BLAS_TRSM_R(scomplex, MKL_Complex8, ctrsm)
#else
EIGEN_BLAS_TRSM_R(double, double, dtrsm_)
EIGEN_BLAS_TRSM_R(dcomplex, double, ztrsm_)
EIGEN_BLAS_TRSM_R(float, float, strsm_)
EIGEN_BLAS_TRSM_R(scomplex, float, ctrsm_)
#endif
} // end namespace internal

View File

@@ -43,12 +43,20 @@
#endif
#pragma clang diagnostic ignored "-Wconstant-logical-operand"
#elif defined __GNUC__ && __GNUC__>=6
#elif defined __GNUC__
#ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
#if (!defined(EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS)) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6))
#pragma GCC diagnostic push
#endif
#pragma GCC diagnostic ignored "-Wignored-attributes"
// g++ warns about local variables shadowing member functions, which is too strict
#pragma GCC diagnostic ignored "-Wshadow"
#if __GNUC__ == 4 && __GNUC_MINOR__ < 8
// Until g++-4.7 there are warnings when comparing unsigned int vs 0, even in templated functions:
#pragma GCC diagnostic ignored "-Wtype-limits"
#endif
#if __GNUC__>=6
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
#endif

View File

@@ -49,10 +49,11 @@
#define EIGEN_USE_LAPACKE
#endif
#if defined(EIGEN_USE_MKL_VML)
#if defined(EIGEN_USE_MKL_VML) && !defined(EIGEN_USE_MKL)
#define EIGEN_USE_MKL
#endif
#if defined EIGEN_USE_MKL
# include <mkl.h>
/*Check IMKL version for compatibility: < 10.3 is not usable with Eigen*/
@@ -108,6 +109,10 @@
#endif
#endif
#if defined(EIGEN_USE_BLAS) && !defined(EIGEN_USE_MKL)
#include "../../misc/blas.h"
#endif
namespace Eigen {
typedef std::complex<double> dcomplex;
@@ -121,8 +126,5 @@ typedef int BlasIndex;
} // end namespace Eigen
#if defined(EIGEN_USE_BLAS)
#include "../../misc/blas.h"
#endif
#endif // EIGEN_MKL_SUPPORT_H

View File

@@ -13,7 +13,7 @@
#define EIGEN_WORLD_VERSION 3
#define EIGEN_MAJOR_VERSION 3
#define EIGEN_MINOR_VERSION 0
#define EIGEN_MINOR_VERSION 6
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -80,8 +80,8 @@
// 2015 14 1900
// "15" 15 1900
/// \internal EIGEN_COMP_MSVC_STRICT set to 1 if the compiler is really Microsoft Visual C++ and not ,e.g., ICC
#if EIGEN_COMP_MSVC && !(EIGEN_COMP_ICC)
/// \internal EIGEN_COMP_MSVC_STRICT set to 1 if the compiler is really Microsoft Visual C++ and not ,e.g., ICC or clang-cl
#if EIGEN_COMP_MSVC && !(EIGEN_COMP_ICC || EIGEN_COMP_LLVM || EIGEN_COMP_CLANG)
#define EIGEN_COMP_MSVC_STRICT _MSC_VER
#else
#define EIGEN_COMP_MSVC_STRICT 0
@@ -356,7 +356,7 @@
#define EIGEN_MAX_CPP_VER 99
#endif
#if EIGEN_MAX_CPP_VER>=11 && defined(__cplusplus) && (__cplusplus >= 201103L)
#if EIGEN_MAX_CPP_VER>=11 && (defined(__cplusplus) && (__cplusplus >= 201103L) || EIGEN_COMP_MSVC >= 1900)
#define EIGEN_HAS_CXX11 1
#else
#define EIGEN_HAS_CXX11 0
@@ -399,7 +399,7 @@
// Does the compiler support variadic templates?
#ifndef EIGEN_HAS_VARIADIC_TEMPLATES
#if EIGEN_MAX_CPP_VER>=11 && (__cplusplus > 199711L || EIGEN_COMP_MSVC >= 1900) \
&& ( !defined(__NVCC__) || !EIGEN_ARCH_ARM_OR_ARM64 || (defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000) )
&& (!defined(__NVCC__) || !EIGEN_ARCH_ARM_OR_ARM64 || (EIGEN_CUDACC_VER >= 80000) )
// ^^ Disable the use of variadic templates when compiling with versions of nvcc older than 8.0 on ARM devices:
// this prevents nvcc from crashing when compiling Eigen on Tegra X1
#define EIGEN_HAS_VARIADIC_TEMPLATES 1
@@ -413,7 +413,7 @@
#ifdef __CUDACC__
// Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above
#if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && defined(__CUDACC_VER__) && (EIGEN_COMP_CLANG || __CUDACC_VER__ >= 70500))
#if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500))
#define EIGEN_HAS_CONSTEXPR 1
#endif
#elif EIGEN_MAX_CPP_VER>=14 && (__has_feature(cxx_relaxed_constexpr) || (defined(__cplusplus) && __cplusplus >= 201402L) || \
@@ -487,20 +487,23 @@
// EIGEN_STRONG_INLINE is a stronger version of the inline, using __forceinline on MSVC,
// but it still doesn't use GCC's always_inline. This is useful in (common) situations where MSVC needs forceinline
// but GCC is still doing fine with just inline.
#ifndef EIGEN_STRONG_INLINE
#if EIGEN_COMP_MSVC || EIGEN_COMP_ICC
#define EIGEN_STRONG_INLINE __forceinline
#else
#define EIGEN_STRONG_INLINE inline
#endif
#endif
// EIGEN_ALWAYS_INLINE is the stronget, it has the effect of making the function inline and adding every possible
// attribute to maximize inlining. This should only be used when really necessary: in particular,
// it uses __attribute__((always_inline)) on GCC, which most of the time is useless and can severely harm compile times.
// FIXME with the always_inline attribute,
// gcc 3.4.x reports the following compilation error:
// gcc 3.4.x and 4.1 reports the following compilation error:
// Eval.h:91: sorry, unimplemented: inlining failed in call to 'const Eigen::Eval<Derived> Eigen::MatrixBase<Scalar, Derived>::eval() const'
// : function body not available
#if EIGEN_GNUC_AT_LEAST(4,0)
// See also bug 1367
#if EIGEN_GNUC_AT_LEAST(4,2)
#define EIGEN_ALWAYS_INLINE __attribute__((always_inline)) inline
#else
#define EIGEN_ALWAYS_INLINE EIGEN_STRONG_INLINE
@@ -811,7 +814,8 @@ namespace Eigen {
// just an empty macro !
#define EIGEN_EMPTY
#if EIGEN_COMP_MSVC_STRICT && (EIGEN_COMP_MSVC < 1900 || __CUDACC_VER__) // for older MSVC versions, as well as 1900 && CUDA 8, using the base operator is sufficient (cf Bugs 1000, 1324)
#if EIGEN_COMP_MSVC_STRICT && (EIGEN_COMP_MSVC < 1900 || EIGEN_CUDACC_VER>0)
// for older MSVC versions, as well as 1900 && CUDA 8, using the base operator is sufficient (cf Bugs 1000, 1324)
#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
using Base::operator =;
#elif EIGEN_COMP_CLANG // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
@@ -985,7 +989,13 @@ namespace Eigen {
# define EIGEN_NOEXCEPT
# define EIGEN_NOEXCEPT_IF(x)
# define EIGEN_NO_THROW throw()
# define EIGEN_EXCEPTION_SPEC(X) throw(X)
# if EIGEN_COMP_MSVC
// MSVC does not support exception specifications (warning C4290),
// and they are deprecated in c++11 anyway.
# define EIGEN_EXCEPTION_SPEC(X) throw()
# else
# define EIGEN_EXCEPTION_SPEC(X) throw(X)
# endif
#endif
#endif // EIGEN_MACROS_H

View File

@@ -70,7 +70,7 @@ inline void throw_std_bad_alloc()
throw std::bad_alloc();
#else
std::size_t huge = static_cast<std::size_t>(-1);
new int[huge];
::operator new(huge);
#endif
}
@@ -150,7 +150,7 @@ EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
/** \internal Allocates \a size bytes. The returned pointer is guaranteed to have 16 or 32 bytes alignment depending on the requirements.
* On allocation error, the returned pointer is null, and std::bad_alloc is thrown.
*/
EIGEN_DEVICE_FUNC inline void* aligned_malloc(size_t size)
EIGEN_DEVICE_FUNC inline void* aligned_malloc(std::size_t size)
{
check_that_malloc_is_allowed();
@@ -185,7 +185,7 @@ EIGEN_DEVICE_FUNC inline void aligned_free(void *ptr)
* \brief Reallocates an aligned block of memory.
* \throws std::bad_alloc on allocation failure
*/
inline void* aligned_realloc(void *ptr, size_t new_size, size_t old_size)
inline void* aligned_realloc(void *ptr, std::size_t new_size, std::size_t old_size)
{
EIGEN_UNUSED_VARIABLE(old_size);
@@ -209,12 +209,12 @@ inline void* aligned_realloc(void *ptr, size_t new_size, size_t old_size)
/** \internal Allocates \a size bytes. If Align is true, then the returned ptr is 16-byte-aligned.
* On allocation error, the returned pointer is null, and a std::bad_alloc is thrown.
*/
template<bool Align> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc(size_t size)
template<bool Align> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc(std::size_t size)
{
return aligned_malloc(size);
}
template<> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc<false>(size_t size)
template<> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc<false>(std::size_t size)
{
check_that_malloc_is_allowed();
@@ -235,12 +235,12 @@ template<> EIGEN_DEVICE_FUNC inline void conditional_aligned_free<false>(void *p
std::free(ptr);
}
template<bool Align> inline void* conditional_aligned_realloc(void* ptr, size_t new_size, size_t old_size)
template<bool Align> inline void* conditional_aligned_realloc(void* ptr, std::size_t new_size, std::size_t old_size)
{
return aligned_realloc(ptr, new_size, old_size);
}
template<> inline void* conditional_aligned_realloc<false>(void* ptr, size_t new_size, size_t)
template<> inline void* conditional_aligned_realloc<false>(void* ptr, std::size_t new_size, std::size_t)
{
return std::realloc(ptr, new_size);
}
@@ -252,7 +252,7 @@ template<> inline void* conditional_aligned_realloc<false>(void* ptr, size_t new
/** \internal Destructs the elements of an array.
* The \a size parameters tells on how many objects to call the destructor of T.
*/
template<typename T> EIGEN_DEVICE_FUNC inline void destruct_elements_of_array(T *ptr, size_t size)
template<typename T> EIGEN_DEVICE_FUNC inline void destruct_elements_of_array(T *ptr, std::size_t size)
{
// always destruct an array starting from the end.
if(ptr)
@@ -262,9 +262,9 @@ template<typename T> EIGEN_DEVICE_FUNC inline void destruct_elements_of_array(T
/** \internal Constructs the elements of an array.
* The \a size parameter tells on how many objects to call the constructor of T.
*/
template<typename T> EIGEN_DEVICE_FUNC inline T* construct_elements_of_array(T *ptr, size_t size)
template<typename T> EIGEN_DEVICE_FUNC inline T* construct_elements_of_array(T *ptr, std::size_t size)
{
size_t i;
std::size_t i;
EIGEN_TRY
{
for (i = 0; i < size; ++i) ::new (ptr + i) T;
@@ -283,9 +283,9 @@ template<typename T> EIGEN_DEVICE_FUNC inline T* construct_elements_of_array(T *
*****************************************************************************/
template<typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void check_size_for_overflow(size_t size)
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void check_size_for_overflow(std::size_t size)
{
if(size > size_t(-1) / sizeof(T))
if(size > std::size_t(-1) / sizeof(T))
throw_std_bad_alloc();
}
@@ -293,7 +293,7 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void check_size_for_overflow(size_t size)
* On allocation error, the returned pointer is undefined, but a std::bad_alloc is thrown.
* The default constructor of T is called.
*/
template<typename T> EIGEN_DEVICE_FUNC inline T* aligned_new(size_t size)
template<typename T> EIGEN_DEVICE_FUNC inline T* aligned_new(std::size_t size)
{
check_size_for_overflow<T>(size);
T *result = reinterpret_cast<T*>(aligned_malloc(sizeof(T)*size));
@@ -309,7 +309,7 @@ template<typename T> EIGEN_DEVICE_FUNC inline T* aligned_new(size_t size)
return result;
}
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new(size_t size)
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new(std::size_t size)
{
check_size_for_overflow<T>(size);
T *result = reinterpret_cast<T*>(conditional_aligned_malloc<Align>(sizeof(T)*size));
@@ -328,7 +328,7 @@ template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned
/** \internal Deletes objects constructed with aligned_new
* The \a size parameters tells on how many objects to call the destructor of T.
*/
template<typename T> EIGEN_DEVICE_FUNC inline void aligned_delete(T *ptr, size_t size)
template<typename T> EIGEN_DEVICE_FUNC inline void aligned_delete(T *ptr, std::size_t size)
{
destruct_elements_of_array<T>(ptr, size);
aligned_free(ptr);
@@ -337,13 +337,13 @@ template<typename T> EIGEN_DEVICE_FUNC inline void aligned_delete(T *ptr, size_t
/** \internal Deletes objects constructed with conditional_aligned_new
* The \a size parameters tells on how many objects to call the destructor of T.
*/
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete(T *ptr, size_t size)
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete(T *ptr, std::size_t size)
{
destruct_elements_of_array<T>(ptr, size);
conditional_aligned_free<Align>(ptr);
}
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_realloc_new(T* pts, size_t new_size, size_t old_size)
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_realloc_new(T* pts, std::size_t new_size, std::size_t old_size)
{
check_size_for_overflow<T>(new_size);
check_size_for_overflow<T>(old_size);
@@ -366,7 +366,7 @@ template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned
}
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new_auto(size_t size)
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new_auto(std::size_t size)
{
if(size==0)
return 0; // short-cut. Also fixes Bug 884
@@ -387,7 +387,7 @@ template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned
return result;
}
template<typename T, bool Align> inline T* conditional_aligned_realloc_new_auto(T* pts, size_t new_size, size_t old_size)
template<typename T, bool Align> inline T* conditional_aligned_realloc_new_auto(T* pts, std::size_t new_size, std::size_t old_size)
{
check_size_for_overflow<T>(new_size);
check_size_for_overflow<T>(old_size);
@@ -409,7 +409,7 @@ template<typename T, bool Align> inline T* conditional_aligned_realloc_new_auto(
return result;
}
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete_auto(T *ptr, size_t size)
template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete_auto(T *ptr, std::size_t size)
{
if(NumTraits<T>::RequireInitialization)
destruct_elements_of_array<T>(ptr, size);
@@ -493,7 +493,7 @@ template<typename T> struct smart_copy_helper<T,true> {
IntPtr size = IntPtr(end)-IntPtr(start);
if(size==0) return;
eigen_internal_assert(start!=0 && end!=0 && target!=0);
memcpy(target, start, size);
std::memcpy(target, start, size);
}
};
@@ -523,7 +523,7 @@ template<typename T> struct smart_memmove_helper<T,true> {
template<typename T> struct smart_memmove_helper<T,false> {
static inline void run(const T* start, const T* end, T* target)
{
if (uintptr_t(target) < uintptr_t(start))
if (UIntPtr(target) < UIntPtr(start))
{
std::copy(start, end, target);
}
@@ -561,7 +561,7 @@ template<typename T> class aligned_stack_memory_handler : noncopyable
* In this case, the buffer elements will also be destructed when this handler will be destructed.
* Finally, if \a dealloc is true, then the pointer \a ptr is freed.
**/
aligned_stack_memory_handler(T* ptr, size_t size, bool dealloc)
aligned_stack_memory_handler(T* ptr, std::size_t size, bool dealloc)
: m_ptr(ptr), m_size(size), m_deallocate(dealloc)
{
if(NumTraits<T>::RequireInitialization && m_ptr)
@@ -576,7 +576,7 @@ template<typename T> class aligned_stack_memory_handler : noncopyable
}
protected:
T* m_ptr;
size_t m_size;
std::size_t m_size;
bool m_deallocate;
};
@@ -655,15 +655,15 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
#if EIGEN_MAX_ALIGN_BYTES!=0
#define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
void* operator new(size_t size, const std::nothrow_t&) EIGEN_NO_THROW { \
void* operator new(std::size_t size, const std::nothrow_t&) EIGEN_NO_THROW { \
EIGEN_TRY { return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); } \
EIGEN_CATCH (...) { return 0; } \
}
#define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) \
void *operator new(size_t size) { \
void *operator new(std::size_t size) { \
return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
} \
void *operator new[](size_t size) { \
void *operator new[](std::size_t size) { \
return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
} \
void operator delete(void * ptr) EIGEN_NO_THROW { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
@@ -673,8 +673,8 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
/* in-place new and delete. since (at least afaik) there is no actual */ \
/* memory allocated we can safely let the default implementation handle */ \
/* this particular case. */ \
static void *operator new(size_t size, void *ptr) { return ::operator new(size,ptr); } \
static void *operator new[](size_t size, void* ptr) { return ::operator new[](size,ptr); } \
static void *operator new(std::size_t size, void *ptr) { return ::operator new(size,ptr); } \
static void *operator new[](std::size_t size, void* ptr) { return ::operator new[](size,ptr); } \
void operator delete(void * memory, void *ptr) EIGEN_NO_THROW { return ::operator delete(memory,ptr); } \
void operator delete[](void * memory, void *ptr) EIGEN_NO_THROW { return ::operator delete[](memory,ptr); } \
/* nothrow-new (returns zero instead of std::bad_alloc) */ \
@@ -696,7 +696,15 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
/** \class aligned_allocator
* \ingroup Core_Module
*
* \brief STL compatible allocator to use with with 16 byte aligned types
* \brief STL compatible allocator to use with types requiring a non standrad alignment.
*
* The memory is aligned as for dynamically aligned matrix/array types such as MatrixXd.
* By default, it will thus provide at least 16 bytes alignment and more in following cases:
* - 32 bytes alignment if AVX is enabled.
* - 64 bytes alignment if AVX512 is enabled.
*
* This can be controled using the \c EIGEN_MAX_ALIGN_BYTES macro as documented
* \link TopicPreprocessorDirectivesPerformance there \endlink.
*
* Example:
* \code
@@ -713,7 +721,7 @@ template<class T>
class aligned_allocator : public std::allocator<T>
{
public:
typedef size_t size_type;
typedef std::size_t size_type;
typedef std::ptrdiff_t difference_type;
typedef T* pointer;
typedef const T* const_pointer;
@@ -739,7 +747,15 @@ public:
pointer allocate(size_type num, const void* /*hint*/ = 0)
{
internal::check_size_for_overflow<T>(num);
return static_cast<pointer>( internal::aligned_malloc(num * sizeof(T)) );
size_type size = num * sizeof(T);
#if EIGEN_COMP_GNUC_STRICT && EIGEN_GNUC_AT_LEAST(7,0)
// workaround gcc bug https://gcc.gnu.org/bugzilla/show_bug.cgi?id=87544
// It triggered eigen/Eigen/src/Core/util/Memory.h:189:12: warning: argument 1 value '18446744073709551612' exceeds maximum object size 9223372036854775807
if(size>=std::size_t((std::numeric_limits<std::ptrdiff_t>::max)()))
return 0;
else
#endif
return static_cast<pointer>( internal::aligned_malloc(size) );
}
void deallocate(pointer p, size_type /*num*/)

View File

@@ -109,6 +109,28 @@ template<> struct is_integral<unsigned int> { enum { value = true }; };
template<> struct is_integral<signed long> { enum { value = true }; };
template<> struct is_integral<unsigned long> { enum { value = true }; };
#if EIGEN_HAS_CXX11
using std::make_unsigned;
#else
// TODO: Possibly improve this implementation of make_unsigned.
// It is currently used only by
// template<typename Scalar> struct random_default_impl<Scalar, false, true>.
template<typename> struct make_unsigned;
template<> struct make_unsigned<char> { typedef unsigned char type; };
template<> struct make_unsigned<signed char> { typedef unsigned char type; };
template<> struct make_unsigned<unsigned char> { typedef unsigned char type; };
template<> struct make_unsigned<signed short> { typedef unsigned short type; };
template<> struct make_unsigned<unsigned short> { typedef unsigned short type; };
template<> struct make_unsigned<signed int> { typedef unsigned int type; };
template<> struct make_unsigned<unsigned int> { typedef unsigned int type; };
template<> struct make_unsigned<signed long> { typedef unsigned long type; };
template<> struct make_unsigned<unsigned long> { typedef unsigned long type; };
#if EIGEN_COMP_MSVC
template<> struct make_unsigned<signed __int64> { typedef unsigned __int64 type; };
template<> struct make_unsigned<unsigned __int64> { typedef unsigned __int64 type; };
#endif
#endif
template <typename T> struct add_const { typedef const T type; };
template <typename T> struct add_const<T&> { typedef T& type; };
@@ -381,12 +403,12 @@ struct has_ReturnType
enum { value = sizeof(testFunctor<T>(0)) == sizeof(meta_yes) };
};
template<typename T> const T& return_ref();
template<typename T> const T* return_ptr();
template <typename T, typename IndexType=Index>
struct has_nullary_operator
{
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ref<C>().operator()())>0)>::type * = 0);
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()())>0)>::type * = 0);
static meta_no testFunctor(...);
enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
@@ -395,7 +417,7 @@ struct has_nullary_operator
template <typename T, typename IndexType=Index>
struct has_unary_operator
{
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ref<C>().operator()(IndexType(0)))>0)>::type * = 0);
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()(IndexType(0)))>0)>::type * = 0);
static meta_no testFunctor(...);
enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
@@ -404,7 +426,7 @@ struct has_unary_operator
template <typename T, typename IndexType=Index>
struct has_binary_operator
{
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ref<C>().operator()(IndexType(0),IndexType(0)))>0)>::type * = 0);
template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()(IndexType(0),IndexType(0)))>0)>::type * = 0);
static meta_no testFunctor(...);
enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
@@ -485,6 +507,26 @@ T div_ceil(const T &a, const T &b)
return (a+b-1) / b;
}
// The aim of the following functions is to bypass -Wfloat-equal warnings
// when we really want a strict equality comparison on floating points.
template<typename X, typename Y> EIGEN_STRONG_INLINE
bool equal_strict(const X& x,const Y& y) { return x == y; }
template<> EIGEN_STRONG_INLINE
bool equal_strict(const float& x,const float& y) { return std::equal_to<float>()(x,y); }
template<> EIGEN_STRONG_INLINE
bool equal_strict(const double& x,const double& y) { return std::equal_to<double>()(x,y); }
template<typename X, typename Y> EIGEN_STRONG_INLINE
bool not_equal_strict(const X& x,const Y& y) { return x != y; }
template<> EIGEN_STRONG_INLINE
bool not_equal_strict(const float& x,const float& y) { return std::not_equal_to<float>()(x,y); }
template<> EIGEN_STRONG_INLINE
bool not_equal_strict(const double& x,const double& y) { return std::not_equal_to<double>()(x,y); }
} // end namespace numext
} // end namespace Eigen

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