Commit Graph

2524 Commits

Author SHA1 Message Date
Jakub Lichman
d87648a6be Tests added and AVX512 bug fixed for pcmp_lt_or_nan 2021-04-25 20:58:56 +00:00
Jakub Lichman
1115f5462e Tests for pcmp_lt and pcmp_le added 2021-04-23 19:51:43 +00:00
Antonio Sanchez
d213a0bcea DenseStorage safely copy/swap.
Fixes #2229.

For dynamic matrices with fixed-sized storage, only copy/swap
elements that have been set.  Otherwise, this leads to inefficient
copying, and potential UB for non-initialized elements.
2021-04-22 18:45:19 +00:00
Antonio Sanchez
69adf26aa3 Modify googlehash use to account for namespace issues.
The namespace declaration for googlehash is a configurable macro that
can be disabled.  In particular, it is disabled within google, causing
compile errors since `dense_hash_map`/`sparse_hash_map` are then in
the global namespace instead of in `::google`.

Here we play a bit of gynastics to allow for both `google::*_hash_map`
and `*_hash_map`, while limiting namespace polution.  Symbols within
the `::google` namespace are imported into `Eigen::google`.

We also remove checks based on `_SPARSE_HASH_MAP_H_`, as this is
fragile, and instead require `EIGEN_GOOGLEHASH_SUPPORT` to be
defined.
2021-04-12 19:00:39 -07:00
Christoph Hertzberg
d58678069c Make iterators default constructible and assignable, by making... 2021-04-09 17:03:28 +00:00
Antonio Sanchez
ace7f132ed Fix clang tidy warnings in AnnoyingScalar.
Clang-tidy complains that full specializations in headers can cause ODR
violations.  Marked these as `inline` to fix.

It also complains about renaming arguments in specializations.  Set the
argument names to match.
2021-04-05 12:49:38 -07:00
Rasmus Munk Larsen
3ddc0974ce Fix two bugs in commit 2021-04-02 22:06:27 +00:00
David Tellenbach
ae95b74af9 Add CMake infrastructure for smoke testing
Necessary CMake changes to implement pre-merge smoke tests
running via CI.
2021-03-31 22:09:00 +00:00
Rasmus Munk Larsen
5bbc9cea93 Add an info() method to the SVDBase class to make it possible to tell the user that the computation failed, possibly due to invalid input.
Make Jacobi and divide-and-conquer fail fast and return info() == InvalidInput if the matrix contains NaN or +/-Inf.
2021-03-31 21:09:19 +00:00
Antonio Sanchez
78ee3d6261 Fix CUDA constexpr issues for numeric_limits.
Some CUDA/HIP constants fail on device with `constexpr` since they
internally rely on non-constexpr functions, e.g.
```
\#define CUDART_INF_F            __int_as_float(0x7f800000)
```
This fails for cuda-clang (though passes with nvcc). These constants are
currently used by `device::numeric_limits`.  For portability, we
need to remove `constexpr` from the affected functions.

For C++11 or higher, we should be able to rely on the `std::numeric_limits`
versions anyways, since the methods themselves are now `constexpr`, so
should be supported on device (clang/hipcc natively, nvcc with
`--expr-relaxed-constexpr`).
2021-03-30 18:01:27 +00:00
Chip Kerchner
d59ef212e1 Fixed performance issues for complex VSX and P10 MMA in gebp_kernel (level 3). 2021-03-25 11:08:19 +00:00
Antonio Sanchez
5521c65afb Eliminate mixingtypes_7 warning.
`g_called` is not used in subtest 7, so was generating a
`-Wunneeded-internal-declaration` warnings.  Here we silence
it by initializing the static variable.
2021-03-24 11:05:41 -07:00
David Tellenbach
0cc9b5eb40 Split test commainitializer into two substests 2021-03-18 13:28:51 +01:00
Antonio Sanchez
c3fbc6cec7 Use singleton pattern for static registered tests.
The original fails with nvcc+msvc - there's a static order of initialization
issue leading to registered tests being cleared.  The test then fails on
```
VERIFY(EigenTest::all().size()>0);
```
since `EigenTest` no longer contains any tests.  The singleton pattern
fixes this.
2021-03-18 00:56:31 +00:00
Antonio Sanchez
8dfe1029a5 Augment NumTraits with min/max_exponent() again.
Replace usage of `std::numeric_limits<...>::min/max_exponent` in
codebase where possible.  Also replaced some other `numeric_limits`
usages in affected tests with the `NumTraits` equivalent.

The previous MR !443 failed for c++03 due to lack of `constexpr`.
Because of this, we need to keep around the `std::numeric_limits`
version in enum expressions until the switch to c++11.

Fixes #2148
2021-03-16 20:12:46 -07:00
David Tellenbach
df4bc2731c Revert "Augment NumTraits with min/max_exponent()."
This reverts commit 75ce9cd2a7.
2021-03-17 03:06:08 +01:00
Antonio Sanchez
75ce9cd2a7 Augment NumTraits with min/max_exponent().
Replace usage of `std::numeric_limits<...>::min/max_exponent` in
codebase.  Also replaced some other `numeric_limits` usages in
affected tests with the `NumTraits` equivalent.

Fixes #2148
2021-03-17 01:00:41 +00:00
Rasmus Munk Larsen
2e83cbbba9 Add NaN propagation options to minCoeff/maxCoeff visitors. 2021-03-16 17:02:50 +00:00
Antonio Sanchez
f612df2736 Add fmod(half, half).
This is to support TensorFlow's `tf.math.floormod` for half.
2021-03-15 13:32:24 -07:00
Antonio Sanchez
d24f9f9b55 Fix NVCC+ICC issues.
NVCC does not understand `__forceinline`, so we need to use `inline`
when compiling for GPU.

ICC specializes `std::complex` operators for `float` and `double`
by default, which cannot be used on device and conflict with Eigen's
workaround in CUDA/Complex.h.  This can be prevented by defining
`_OVERRIDE_COMPLEX_SPECIALIZATION_` before including `<complex>`.
Added this define to the tests and to `Eigen/Core`, but this will
not work if the user includes `<complex>` before `<Eigen/Core>`.

ICC also seems to generate a duplicate `Map` symbol in
`PlainObjectBase`:
```
error: "Map" has already been declared in the current scope
  static ConstMapType Map(const Scalar *data)

```
I tracked this down to `friend class Eigen::Map`.  Putting the `friend`
statements at the bottom of the class seems to resolve this issue.

Fixes #2180
2021-03-15 18:42:04 +00:00
Antonio Sanchez
14487ed14e Add increment/decrement operators to Eigen::half.
This is for consistency with bfloat16, and to support initialization
with `std::iota`.
2021-03-15 10:52:23 -07:00
Antonio Sanchez
b271110788 Bump up rand histogram threshold.
The previous one sometimes fails for MSVC which has a poor random
number generator.

Fixes #2182
2021-03-10 22:17:03 -08:00
Antonio Sanchez
543e34ab9d Re-implement move assignments.
The original swap approach leads to potential undefined behavior (reading
uninitialized memory) and results in unnecessary copying of data for static
storage.

Here we pass down the move assignment to the underlying storage.  Static
storage does a one-way copy, dynamic storage does a swap.

Modified the tests to no longer read from the moved-from matrix/tensor,
since that can lead to UB. Added a test to ensure we do not access
uninitialized memory in a move.

Fixes: #2119
2021-03-10 16:55:20 +00:00
Antonio Sanchez
2468253c9a Define EIGEN_CPLUSPLUS and replace most __cplusplus checks.
The macro `__cplusplus` is not defined correctly in MSVC unless building
with the the `/Zc:__cplusplus` flag. Instead, it defines `_MSVC_LANG` to the
specified c++ standard version number.

Here we introduce `EIGEN_CPLUSPLUS` which will contain the c++ version
number both for MSVC and otherwise.  This simplifies checks for supported
features.

Also replaced most instances of standard version checking via `__cplusplus`
with the existing `EIGEN_COMP_CXXVER` macro for better clarity.

Fixes: #2170
2021-03-05 18:33:18 +00:00
Antonio Sanchez
82d61af3a4 Fix rint SSE/NEON again, using optimization barrier.
This is a new version of !423, which failed for MSVC.

Defined `EIGEN_OPTIMIZATION_BARRIER(X)` that uses inline assembly to
prevent operations involving `X` from crossing that barrier. Should
work on most `GNUC` compatible compilers (MSVC doesn't seem to need
this). This is a modified version adapted from what was used in
`psincos_float` and tested on more platforms
(see #1674, https://godbolt.org/z/73ezTG).

Modified `rint` to use the barrier to prevent the add/subtract rounding
trick from being optimized away.

Also fixed an edge case for large inputs that get bumped up a power of two
and ends up rounding away more than just the fractional part.  If we are
over `2^digits` then just return the input.  This edge case was missed in
the test since the test was comparing approximate equality, which was still
satisfied.  Adding a strict equality option catches it.
2021-03-05 08:54:12 -08:00
Antonio Sánchez
9a663973b4 Revert "Fix rint for SSE/NEON."
This reverts commit e72dfeb8b9
2021-03-03 18:51:51 +00:00
Antonio Sanchez
e72dfeb8b9 Fix rint for SSE/NEON.
It seems *sometimes* with aggressive optimizations the combination
`psub(padd(a, b), b)` trick to force rounding is compiled away. Here
we replace with inline assembly to prevent this (I tried `volatile`,
but that leads to additional loads from memory).

Also fixed an edge case for large inputs `a` where adding `b` bumps
the value up a power of two and ends up rounding away more than
just the fractional part.  If we are over `2^digits` then just return
the input.  This edge case was missed in the test since the test was
comparing approximate equality, which was still satisfied.  Adding
a strict equality option catches it.
2021-03-03 09:41:46 -08:00
Christoph Hertzberg
199c5f2b47 geo_alignedbox_5 was failing with AVX enabled, due to storing Vector4d in a std::vector without using an aligned allocator.
Got rid of using `std::vector` and simplified the code.
Avoid leading `_`
2021-03-01 03:59:21 +01:00
Antonio Sanchez
1e0c7d4f49 Add print for SSE/NEON, use NEON rounding intrinsics if available.
In SSE, by adding/subtracting 2^MantissaBits, we force rounding according to the
current rounding mode.

For NEON, we use the provided intrinsics for rint/floor/ceil if
available (armv8).

Related to #1969.
2021-02-27 22:42:07 +00:00
Antonio Sanchez
c65c2b31d4 Make half/bfloat16 constructor take inputs by value, fix powerpc test.
Since `numeric_limits<half>::max_exponent` is a static inline constant,
it cannot be directly passed by reference. This triggers a linker error
in recent versions of `g++-powerpc64le`.

Changing `half` to take inputs by value fixes this.  Wrapping
`max_exponent` with `int(...)` to make an addressable integer also fixes this
and may help with other custom `Scalar` types down-the-road.

Also eliminated some compile warnings for powerpc.
2021-02-27 21:32:06 +00:00
Christoph Hertzberg
ca528593f4 Fixed/masked more implicit copy constructor warnings
(cherry picked from commit 2883e91ce5a99c391fbf28e20160176b70854992)
2021-02-27 18:44:26 +01:00
Antonio Sanchez
29ebd84cb7 Fix NEON sqrt for 32-bit, add prsqrt.
With !406, we accidentally broke arm 32-bit NEON builds, since
`vsqrt_f32` is only available for 64-bit.

Here we add back the `rsqrt` implementation for 32-bit, relying
on a `prsqrt` implementation with better handling of edge cases.

Note that several of the 32-bit NEON packet tests are currently
failing - either due to denormal handling (NEON versions flush
to zero, but scalar paths don't) or due to accuracy (e.g. sin/cos).
2021-02-26 14:08:40 -08:00
Rasmus Munk Larsen
fe19714f80 Merge branch 'rmlarsen1/eigen-nan_prop' 2021-02-26 09:21:24 -08:00
Antonio Sanchez
e19829c3b0 Fix floor/ceil for NEON fp16.
Forgot to test this.  Fixes bug introduced in !416.
2021-02-25 20:39:56 -08:00
Antonio Sanchez
5529db7524 Fix SSE/NEON pfloor/pceil for saturated values.
The original will saturate if the input does not fit into an integer
type.  Here we fix this, returning the input if it doesn't have
enough precision to have a fractional part.

Also added `pceil` for NEON.

Fixes #1969.
2021-02-25 14:39:26 -08:00
Rasmus Munk Larsen
5297b7162a Make it possible to specify NaN propagation strategy for maxCoeff/minCoeff reductions. 2021-02-25 18:21:21 +00:00
Antonio Sanchez
ecb7b19dfa Disable new/delete test for HIP 2021-02-25 08:04:05 -08:00
Antonio Sanchez
5908aeeaba Fix CUDA device new and delete, and add test.
HIP does not support new/delete on device, so test is skipped.
2021-02-24 11:31:41 -08:00
Antonio Sanchez
119763cf38 Eliminate CMake FindPackageHandleStandardArgs warnings.
CMake complains that the package name does not match when the case
differs, e.g.:
```
CMake Warning (dev) at /usr/share/cmake-3.18/Modules/FindPackageHandleStandardArgs.cmake:273 (message):
  The package name passed to `find_package_handle_standard_args` (UMFPACK)
  does not match the name of the calling package (Umfpack).  This can lead to
  problems in calling code that expects `find_package` result variables
  (e.g., `_FOUND`) to follow a certain pattern.
Call Stack (most recent call first):
  cmake/FindUmfpack.cmake:50 (find_package_handle_standard_args)
  bench/spbench/CMakeLists.txt:24 (find_package)
This warning is for project developers.  Use -Wno-dev to suppress it.
```
Here we rename the libraries to match their true cases.
2021-02-24 09:52:05 +00:00
Adam Shapiro
2ac0b78739 Fixed sparse conservativeResize() when both num cols and rows decreased.
The previous implementation caused a buffer overflow trying to calculate non-
zero counts for columns that no longer exist.
2021-02-23 21:32:39 +00:00
Christoph Hertzberg
ce4af0b38f Missing change regarding #1910 2021-02-19 20:51:35 +01:00
Christoph Hertzberg
a7749c09bc Bug #1910: Make SparseCholesky work for RowMajor matrices 2021-02-19 19:36:18 +01:00
Rasmus Munk Larsen
be0574e215 New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double. 2021-02-17 02:50:32 +00:00
Antonio Sanchez
7ff0b7a980 Updated pfrexp implementation.
The original implementation fails for 0, denormals, inf, and NaN.

See #2150
2021-02-17 02:23:24 +00:00
Antonio Sanchez
4cb563a01e Fix ldexp implementations.
The previous implementations produced garbage values if the exponent did
not fit within the exponent bits.  See #2131 for a complete discussion,
and !375 for other possible implementations.

Here we implement the 4-factor version. See `pldexp_impl` in
`GenericPacketMathFunctions.h` for a full description.

The SSE `pcmp*` methods were moved down since `pcmp_le<Packet4i>`
requires `por`.

Left as a "TODO" is to delegate to a faster version if we know the
exponent does fit within the exponent bits.

Fixes #2131.
2021-02-10 22:45:41 +00:00
Ralf Hannemann-Tamas
984d010b7b add specialization of check_sparse_solving() for SuperLU solver, in order to test adjoint and transpose solves 2021-02-08 22:00:31 +00:00
Rasmus Munk Larsen
6e3b795f81 Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one. 2021-02-05 16:58:49 -08:00
Gael Guennebaud
0668c68b03 Allow for negative strides.
Note that using a stride of -1 is still not possible because it would
clash with the definition of Eigen::Dynamic.

This fixes #747.
2021-01-27 23:32:12 +01:00
Samir Benmendil
288d456c29 Replace language_support module with builtin CheckLanguage
The workaround_9220 function was introduced a long time ago to
workaround a CMake issue with enable_language(OPTIONAL). Since then
CMake has clarified that the OPTIONAL keywords has not been
implemented[0].

A CheckLanguage module is now provided with CMake to check if a language
can be enabled. Use that instead.

[0] https://cmake.org/cmake/help/v3.18/command/enable_language.html
2021-01-27 13:26:40 +00:00
Antonio Sanchez
4c42d5ee41 Eliminate implicit conversion warning in test/array_cwise.cpp 2021-01-23 11:54:00 -08:00
Antonio Sanchez
e0d13ead90 Replace std::isnan with numext::isnan for c++03 2021-01-23 11:02:35 -08:00
Antonio Sanchez
f0e46ed5d4 Fix pow and other cwise ops for half/bfloat16.
The new `generic_pow` implementation was failing for half/bfloat16 since
their construction from int/float is not `constexpr`. Modified
in `GenericPacketMathFunctions` to remove `constexpr`.

While adding tests for half/bfloat16, found other issues related to
implicit conversions.

Also needed to implement `numext::arg` for non-integer, non-complex,
non-float/double/long double types.  These seem to be  implicitly
converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-22 11:10:54 -08:00
Antonio Sanchez
f19bcffee6 Specialize std::complex operators for use on GPU device.
NVCC and older versions of clang do not fully support `std::complex` on device,
leading to either compile errors (Cannot call `__host__` function) or worse,
runtime errors (Illegal instruction).  For most functions, we can
implement specialized `numext` versions. Here we specialize the standard
operators (with the exception of stream operators and member function operators
with a scalar that are already specialized in `<complex>`) so they can be used
in device code as well.

To import these operators into the current scope, use
`EIGEN_USING_STD_COMPLEX_OPERATORS`. By default, these are imported into
the `Eigen`, `Eigen:internal`, and `Eigen::numext` namespaces.

This allow us to remove specializations of the
sum/difference/product/quotient ops, and allow us to treat complex
numbers like most other scalars (e.g. in tests).
2021-01-22 18:19:19 +00:00
Antonio Sanchez
b2126fd6b5 Fix pfrexp/pldexp for half.
The recent addition of vectorized pow (!330) relies on `pfrexp` and
`pldexp`.  This was missing for `Eigen::half` and `Eigen::bfloat16`.
Adding tests for these packet ops also exposed an issue with handling
negative values in `pfrexp`, returning an incorrect exponent.

Added the missing implementations, corrected the exponent in `pfrexp1`,
and added `packetmath` tests.
2021-01-21 19:32:28 +00:00
Antonio Sanchez
25d8498f8b Fix stable_norm_1 test.
Test enters an infinite loop if size is 1x1 when choosing to select
unique indices for adding `inf` and `NaN` to the input. Here we
revert to non-unique indices, and split the `hypotNorm` check into
two cases: one where both `inf` and `NaN` are added, and one where
only `NaN` is added.
2021-01-21 09:44:42 -08:00
Rasmus Munk Larsen
cdd8fdc32e Vectorize pow(x, y). This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm.
I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics:

```
max_rel_error = 8.34405e-07
rms_rel_error = 2.76654e-07
```

If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`:

```
max_rel_error = 0.666667
rms = 6.8727e-05
count = 1335165689
argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45
```

which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 13:25:16 +00:00
Antonio Sanchez
bde6741641 Improved std::complex sqrt and rsqrt.
Replaces `std::sqrt` with `complex_sqrt` for all platforms (previously
`complex_sqrt` was only used for CUDA and MSVC), and implements
custom `complex_rsqrt`.

Also introduces `numext::rsqrt` to simplify implementation, and modified
`numext::hypot` to adhere to IEEE IEC 6059 for special cases.

The `complex_sqrt` and `complex_rsqrt` implementations were found to be
significantly faster than `std::sqrt<std::complex<T>>` and
`1/numext::sqrt<std::complex<T>>`.

Benchmark file attached.
```
GCC 10, Intel Xeon, x86_64:
---------------------------------------------------------------------------
Benchmark                                 Time             CPU   Iterations
---------------------------------------------------------------------------
BM_Sqrt<std::complex<float>>           9.21 ns         9.21 ns     73225448
BM_StdSqrt<std::complex<float>>        17.1 ns         17.1 ns     40966545
BM_Sqrt<std::complex<double>>          8.53 ns         8.53 ns     81111062
BM_StdSqrt<std::complex<double>>       21.5 ns         21.5 ns     32757248
BM_Rsqrt<std::complex<float>>          10.3 ns         10.3 ns     68047474
BM_DivSqrt<std::complex<float>>        16.3 ns         16.3 ns     42770127
BM_Rsqrt<std::complex<double>>         11.3 ns         11.3 ns     61322028
BM_DivSqrt<std::complex<double>>       16.5 ns         16.5 ns     42200711

Clang 11, Intel Xeon, x86_64:
---------------------------------------------------------------------------
Benchmark                                 Time             CPU   Iterations
---------------------------------------------------------------------------
BM_Sqrt<std::complex<float>>           7.46 ns         7.45 ns     90742042
BM_StdSqrt<std::complex<float>>        16.6 ns         16.6 ns     42369878
BM_Sqrt<std::complex<double>>          8.49 ns         8.49 ns     81629030
BM_StdSqrt<std::complex<double>>       21.8 ns         21.7 ns     31809588
BM_Rsqrt<std::complex<float>>          8.39 ns         8.39 ns     82933666
BM_DivSqrt<std::complex<float>>        14.4 ns         14.4 ns     48638676
BM_Rsqrt<std::complex<double>>         9.83 ns         9.82 ns     70068956
BM_DivSqrt<std::complex<double>>       15.7 ns         15.7 ns     44487798

Clang 9, Pixel 2, aarch64:
---------------------------------------------------------------------------
Benchmark                                 Time             CPU   Iterations
---------------------------------------------------------------------------
BM_Sqrt<std::complex<float>>           24.2 ns         24.1 ns     28616031
BM_StdSqrt<std::complex<float>>         104 ns          103 ns      6826926
BM_Sqrt<std::complex<double>>          31.8 ns         31.8 ns     22157591
BM_StdSqrt<std::complex<double>>        128 ns          128 ns      5437375
BM_Rsqrt<std::complex<float>>          31.9 ns         31.8 ns     22384383
BM_DivSqrt<std::complex<float>>        99.2 ns         98.9 ns      7250438
BM_Rsqrt<std::complex<double>>         46.0 ns         45.8 ns     15338689
BM_DivSqrt<std::complex<double>>        119 ns          119 ns      5898944
```
2021-01-17 08:50:57 -08:00
Antonio Sanchez
f149e0ebc3 Fix MSVC complex sqrt and packetmath test.
MSVC incorrectly handles `inf` cases for `std::sqrt<std::complex<T>>`.
Here we replace it with a custom version (currently used on GPU).

Also fixed the `packetmath` test, which previously skipped several
corner cases since `CHECK_CWISE1` only tests the first `PacketSize`
elements.
2021-01-08 01:17:19 +00:00
Antonio Sanchez
8d9cfba799 Fix rand test for MSVC.
MSVC's uniform random number generator is not quite as uniform as
others, requiring a slightly wider threshold on the histogram test.
After inspecting histograms for several runs, there's no obvious
bias -- just some bins end up having slightly more less elements
(often > 2% but less than 2.5%).
2021-01-07 12:48:40 -08:00
Essex Edwards
e741b43668 Make Transform::computeRotationScaling(0,&S) continuous 2021-01-07 17:45:14 +00:00
Antonio Sanchez
bb1de9dbde Fix Ref Stride checks.
The existing `Ref` class failed to consider cases where the Ref's
`Stride` setting *could* match the underlying referred object's stride,
but **didn't** at runtime.  This led to trying to set invalid stride values,
causing runtime failures in some cases, and garbage due to mismatched
strides in others.

Here we add the missing runtime checks.  This involves computing the
strides necessary to align with the referred object's storage, and
verifying we can actually set those strides at runtime.

In the `const` case, if it *may* be possible to refer to the original
storage at compile-time but fails at runtime, then we defer to the
`construct(...)` method that makes a copy.

Added more tests to check these cases.

Fixes #2093.
2021-01-05 10:41:25 -08:00
Christoph Hertzberg
12dda34b15 Eliminate boolean product warnings by factoring out a
`combine_scalar_factors` helper function.
2021-01-05 18:15:30 +00:00
Antonio Sanchez
070d303d56 Add CUDA complex sqrt.
This is to support scalar `sqrt` of complex numbers `std::complex<T>` on
device, requested by Tensorflow folks.

Technically `std::complex` is not supported by NVCC on device
(though it is by clang), so the default `sqrt(std::complex<T>)` function only
works on the host. Here we create an overload to add back the
functionality.

Also modified the CMake file to add `--relaxed-constexpr` (or
equivalent) flag for NVCC to allow calling constexpr functions from
device functions, and added support for specifying compute architecture for
NVCC (was already available for clang).
2020-12-22 23:25:23 -08:00
Antonio Sanchez
c6efc4e0ba Replace M_LOG2E and M_LN2 with custom macros.
For these to exist we would need to define `_USE_MATH_DEFINES` before
`cmath` or `math.h` is first included.  However, we don't
control the include order for projects outside Eigen, so even defining
the macro in `Eigen/Core` does not fix the issue for projects that
end up including `<cmath>` before Eigen does (explicitly or transitively).

To fix this, we define `EIGEN_LOG2E` and `EIGEN_LN2` ourselves.
2020-12-11 14:34:31 -08:00
Rasmus Munk Larsen
125cc9a5df Implement vectorized complex square root.
Closes #1905

Measured speedup for sqrt of `complex<float>` on Skylake:

SSE:
```
name                      old time/op             new time/op  delta
BM_eigen_sqrt_ctype/1     49.4ns ± 0%             54.3ns ± 0%  +10.01%
BM_eigen_sqrt_ctype/8      332ns ± 0%               50ns ± 1%  -84.97%
BM_eigen_sqrt_ctype/64    2.81µs ± 1%             0.38µs ± 0%  -86.49%
BM_eigen_sqrt_ctype/512   23.8µs ± 0%              3.0µs ± 0%  -87.32%
BM_eigen_sqrt_ctype/4k     202µs ± 0%               24µs ± 2%  -88.03%
BM_eigen_sqrt_ctype/32k   1.63ms ± 0%             0.19ms ± 0%  -88.18%
BM_eigen_sqrt_ctype/256k  13.0ms ± 0%              1.5ms ± 1%  -88.20%
BM_eigen_sqrt_ctype/1M    52.1ms ± 0%              6.2ms ± 0%  -88.18%
```

AVX2:
```
name                      old cpu/op  new cpu/op  delta
BM_eigen_sqrt_ctype/1     53.6ns ± 0%  55.6ns ± 0%   +3.71%
BM_eigen_sqrt_ctype/8      334ns ± 0%    27ns ± 0%  -91.86%
BM_eigen_sqrt_ctype/64    2.79µs ± 0%  0.22µs ± 2%  -92.28%
BM_eigen_sqrt_ctype/512   23.8µs ± 1%   1.7µs ± 1%  -92.81%
BM_eigen_sqrt_ctype/4k     201µs ± 0%    14µs ± 1%  -93.24%
BM_eigen_sqrt_ctype/32k   1.62ms ± 0%  0.11ms ± 1%  -93.29%
BM_eigen_sqrt_ctype/256k  13.0ms ± 0%   0.9ms ± 1%  -93.31%
BM_eigen_sqrt_ctype/1M    52.0ms ± 0%   3.5ms ± 1%  -93.31%
```

AVX512:
```
name                      old cpu/op  new cpu/op  delta
BM_eigen_sqrt_ctype/1     53.7ns ± 0%  56.2ns ± 1%   +4.75%
BM_eigen_sqrt_ctype/8      334ns ± 0%    18ns ± 2%  -94.63%
BM_eigen_sqrt_ctype/64    2.79µs ± 0%  0.12µs ± 1%  -95.54%
BM_eigen_sqrt_ctype/512   23.9µs ± 1%   1.0µs ± 1%  -95.89%
BM_eigen_sqrt_ctype/4k     202µs ± 0%     8µs ± 1%  -96.13%
BM_eigen_sqrt_ctype/32k   1.63ms ± 0%  0.06ms ± 1%  -96.15%
BM_eigen_sqrt_ctype/256k  13.0ms ± 0%   0.5ms ± 4%  -96.11%
BM_eigen_sqrt_ctype/1M    52.1ms ± 0%   2.0ms ± 1%  -96.13%
```
2020-12-08 18:13:35 -08:00
Rasmus Munk Larsen
f9fac1d5b0 Add log2() to Eigen. 2020-12-04 21:45:09 +00:00
Rasmus Munk Larsen
f23dc5b971 Revert "Add log2() operator to Eigen"
This reverts commit 4d91519a9b.
2020-12-03 14:32:45 -08:00
Rasmus Munk Larsen
4d91519a9b Add log2() operator to Eigen 2020-12-03 22:31:44 +00:00
Antonio Sanchez
eb4d4ae070 Include chrono in main for c++11.
Hack to fix tensor tests, since min/max are overridden by `main.h`.
2020-12-03 11:27:32 -08:00
Antonio Sanchez
89f90b585d AVX512 missing ops.
This allows the `packetmath` tests to pass for AVX512 on skylake.
Made `half` and `bfloat16` consistent in terms of ops they support.

Note the `log` tests are currently disabled for `bfloat16` since
they fail due to poor precision (they were previously disabled for
`Packet8bf` via test function specialization -- I just removed that
specialization and disabled it in the generic test).
2020-11-30 16:28:57 +00:00
Bowie Owens
9842366bba Make inclusion of doc sub-directory optional by adjusting options.
Allows exclusion of doc and related targets to help when using eigen via add_subdirectory().

Requested by:

https://gitlab.com/libeigen/eigen/-/issues/1842

Also required making EIGEN_TEST_BUILD_DOCUMENTATION a dependent option on EIGEN_BUILD_DOC. This ensures documentation targets are properly defined when EIGEN_TEST_BUILD_DOCUMENTATION is ON.
2020-11-27 08:11:49 +11:00
Rasmus Munk Larsen
79818216ed Revert "Fix Half NaN definition and test."
This reverts commit c770746d70.
2020-11-24 12:57:28 -08:00
Rasmus Munk Larsen
c770746d70 Fix Half NaN definition and test.
The `half_float` test was failing with `-mcpu=cortex-a55` (native `__fp16`) due
to a bad NaN bit-pattern comparison (in the case of casting a float to `__fp16`,
the signaling `NaN` is quieted). There was also an inconsistency between
`numeric_limits<half>::quiet_NaN()` and `NumTraits::quiet_NaN()`.  Here we
correct the inconsistency and compare NaNs according to the IEEE 754
definition.

Also modified the `bfloat16_float` test to match.

Tested with `cortex-a53` and `cortex-a55`.
2020-11-24 20:53:07 +00:00
Antonio Sanchez
a3b300f1af Implement missing AVX half ops.
Minimal implementation of AVX `Eigen::half` ops to bring in line
with `bfloat16`.  Allows `packetmath_13` to pass.

Also adjusted `bfloat16` packet traits to match the supported set
of ops (e.g. Bessel is not actually implemented).
2020-11-24 16:46:41 +00:00
Antonio Sanchez
38abf2be42 Fix Half NaN definition and test.
The `half_float` test was failing with `-mcpu=cortex-a55` (native `__fp16`) due
to a bad NaN bit-pattern comparison (in the case of casting a float to `__fp16`,
the signaling `NaN` is quieted). There was also an inconsistency between
`numeric_limits<half>::quiet_NaN()` and `NumTraits::quiet_NaN()`.  Here we
correct the inconsistency and compare NaNs according to the IEEE 754
definition.

Also modified the `bfloat16_float` test to match.

Tested with `cortex-a53` and `cortex-a55`.
2020-11-23 14:13:59 -08:00
Antonio Sanchez
4cf01d2cf5 Update AVX half packets, disable test.
The AVX half implementation is incomplete, causing the `packetmath_13` test
to fail.  This disables the test.

Also refactored the existing AVX implementation to use `bit_cast`
instead of direct access to `.x`.
2020-11-21 09:05:10 -08:00
Antonio Sanchez
a8fdcae55d Fix sparse_extra_3, disable counting temporaries for testing DynamicSparseMatrix.
Multiplication of column-major `DynamicSparseMatrix`es involves three
temporaries:
- two for transposing twice to sort the coefficients
(`ConservativeSparseSparseProduct.h`, L160-161)
- one for a final copy assignment (`SparseAssign.h`, L108)
The latter is avoided in an optimization for `SparseMatrix`.

Since `DynamicSparseMatrix` is deprecated in favor of `SparseMatrix`, it's not
worth the effort to optimize further, so I simply disabled counting
temporaries via a macro.

Note that due to the inclusion of `sparse_product.cpp`, the `sparse_extra`
tests actually re-run all the original `sparse_product` tests as well.

We may want to simply drop the `DynamicSparseMatrix` tests altogether, which
would eliminate the test duplication.

Related to #2048
2020-11-18 23:15:33 +00:00
David Tellenbach
11e4056f6b Re-enable Arm Neon Eigen::half packets of size 8
- Add predux_half_dowto4
- Remove explicit casts in Half.h to match the behaviour of BFloat16.h
- Enable more packetmath tests for Eigen::half
2020-11-18 23:02:21 +00:00
Antonio Sanchez
17268b155d Add bit_cast for half/bfloat to/from uint16_t, fix TensorRandom
The existing `TensorRandom.h` implementation makes the assumption that
`half` (`bfloat16`) has a `uint16_t` member `x` (`value`), which is not
always true. This currently fails on arm64, where `x` has type `__fp16`.
Added `bit_cast` specializations to allow casting to/from `uint16_t`
for both `half` and `bfloat16`.  Also added tests in
`half_float`, `bfloat16_float`, and `cxx11_tensor_random` to catch
these errors in the future.
2020-11-18 20:32:35 +00:00
Antonio Sanchez
41d5d5334b Initialize primitives to fix -Wuninitialized-const-reference.
The `meta` test generates warnings with the latest version of clang due
to passing uninitialized variables as const reference arguments.
```
test/meta.cpp:102:45: error: variable 'f' is uninitialized when passed as a const reference argument here [-Werror,-Wuninitialized-const-reference]
    VERIFY(( check_is_convertible(a.dot(b), f) ));
```
We don't actually use the variables, but initializing them eliminates the
new warning.

Fixes #2067.
2020-11-18 20:23:20 +00:00
Antonio Sanchez
8e9cc5b10a Eliminate double-promotion warnings.
Clang currently complains about implicit conversions, e.g.
```
test/packetmath.cpp:680:59: warning: implicit conversion increases floating-point precision: 'typename Eigen::internal::random_retval<typename Eigen::internal::global_math_functions_filtering_base<double>::type>::type' (aka 'double') to 'long double' [-Wdouble-promotion]
          data1[0] = Scalar((2 * k + k1) * EIGEN_PI / 2 * internal::random<double>(0.8, 1.2));
                                                        ~ ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
test/packetmath.cpp:681:40: warning: implicit conversion increases floating-point precision: 'float' to 'long double' [-Wdouble-promotion]
          data1[1] = Scalar((2 * k + 2 + k1) * EIGEN_PI / 2 * internal::random<double>(0.8, 1.2));
```

Modified to explicitly cast to double.
2020-11-16 10:39:09 -08:00
Antonio Sanchez
bb69a8db5d Explicit casts of S -> std::complex<T>
When calling `internal::cast<S, std::complex<T>>(x)`, clang often
generates an implicit conversion warning due to an implicit cast
from type `S` to `T`.  This currently affects the following tests:
- `basicstuff`
- `bfloat16_float`
- `cxx11_tensor_casts`

The implicit cast leads to widening/narrowing float conversions.
Widening warnings only seem to be generated by clang (`-Wdouble-promotion`).

To eliminate the warning, we explicitly cast the real-component first
from `S` to `T`.  We also adjust tests to use `internal::cast` instead
of `static_cast` when a complex type may be involved.
2020-11-14 05:50:42 +00:00
Christoph Hertzberg
90f6d9d23e Suppress ignored-attributes warning (same as in vectorization_logic). Remove redundant include and using namespace. 2020-11-13 16:21:53 +01:00
Everton Constantino
348a48682e Fix erroneous forward declaration of boost nvp. 2020-11-10 13:07:34 -03:00
Deven Desai
9d11e2c03e CMakefile update for ROCm 4.0
Starting with ROCm 4.0, the `hipconfig --platform` command will return `amd` (prior return value was `hcc`). Updating the CMakeLists.txt files in the test dirs to account for this change.
2020-10-29 18:06:31 +00:00
David Tellenbach
e265f7ed8e Add support for Armv8.2-a __fp16
Armv8.2-a provides a native half-precision floating point (__fp16 aka.
float16_t). This patch introduces

* __fp16 as underlying type of Eigen::half if this type is available
* the packet types Packet4hf and Packet8hf representing float16x4_t and
  float16x8_t respectively
* packet-math for the above packets with corresponding scalar type Eigen::half

The packet-math functionality has been implemented by Ashutosh Sharma
<ashutosh.sharma@amperecomputing.com>.

This closes #1940.
2020-10-28 20:15:09 +00:00
Rasmus Munk Larsen
c6953f799b Add packet generic ops predux_fmin, predux_fmin_nan, predux_fmax, and predux_fmax_nan that implement reductions with PropagateNaN, and PropagateNumbers semantics. Add (slow) generic implementations for most reductions. 2020-10-13 21:48:31 +00:00
Rasmus Munk Larsen
4e4d3f32d1 Clean up packetmath tests and fix various bugs to make bfloat16 pass (almost) all packetmath tests with SSE, AVX, and AVX512. 2020-10-09 20:05:49 +00:00
David Tellenbach
7a8d3d5b81 Disable test exceptions when using OpenMP. 2020-10-09 17:49:07 +02:00
Rasmus Munk Larsen
b431024404 Don't make assumptions about NaN-propagation for pmin/pmax - it various across platforms.
Change test to only test for NaN-propagation for pfmin/pfmax.
2020-10-07 19:05:18 +00:00
Rasmus Munk Larsen
3b445d9bf2 Add a generic packet ops corresponding to {std}::fmin and {std}::fmax. The non-sensical NaN-propagation rules for std::min std::max implemented by pmin and pmax in Eigen is a longstanding source og confusion and bug report. This change is a first step towards addressing it, as discussing in issue #564. 2020-10-01 16:54:31 +00:00
Antonio Sanchez
d5a0d89491 Fix alignedbox 32-bit precision test failure.
The current `test/geo_alignedbox` tests fail on 32-bit arm due to small floating-point errors.

In particular, the following is not guaranteed to hold:
```
IsometryTransform identity = IsometryTransform::Identity();
BoxType transformedC;
transformedC.extend(c.transformed(identity));
VERIFY(transformedC.contains(c));
```
since `c.transformed(identity)` is ever-so-slightly different from `c`. Instead, we replace this test with one that checks an identity transform is within floating-point precision of `c`.

Also updated the condition on `AlignedBox::transform(...)` to only accept `Affine`, `AffineCompact`, and `Isometry` modes explicitly.  Otherwise, invalid combinations of modes would also incorrectly pass the assertion.
2020-09-30 08:42:03 -07:00
Martin Pecka
6425e875a1 Added AlignedBox::transform(AffineTransform). 2020-09-28 18:06:23 +00:00
David Tellenbach
493a7c773c Remove EIGEN_CONSTEXPR from NumTraits<boost::multiprecision::number<...>> 2020-09-21 12:43:41 +02:00
Rasmus Munk Larsen
e55182ac09 Get rid of initialization logic for blueNorm by making the computed constants static const or constexpr.
Move macro definition EIGEN_CONSTEXPR to Core and make all methods in NumTraits constexpr when EIGEN_HASH_CONSTEXPR is 1.
2020-09-18 17:38:58 +00:00
Tim Shen
bb56a62582 Make bfloat16(float(-nan)) produce -nan, not nan. 2020-09-15 13:24:23 -07:00
Pedro Caldeira
35d149e34c Add missing functions for Packet8bf in Altivec architecture.
Including new tests for bfloat16 Packets.
Fix prsqrt on GenericPacketMath.
2020-09-08 09:22:11 -05:00
Everton Constantino
6fe88a3c9d MatrixProuct enhancements:
- Changes to Altivec/MatrixProduct
  Adapting code to gcc 10.
  Generic code style and performance enhancements.
  Adding PanelMode support.
  Adding stride/offset support.
  Enabling float64, std::complex and std::complex.
  Fixing lack of symm_pack.
  Enabling mixedtypes.
- Adding std::complex tests to blasutil.
- Adding an implementation of storePacketBlock when Incr!= 1.
2020-09-02 18:21:36 -03:00
Gael Guennebaud
25424d91f6 Fix #1974: assertion when reserving an empty sparse matrix 2020-08-26 12:32:20 +02:00
Deven Desai
603e213d13 Fixing a CUDA / P100 regression introduced by PR 181
PR 181 ( https://gitlab.com/libeigen/eigen/-/merge_requests/181 ) adds `__launch_bounds__(1024)` attribute to GPU kernels, that did not have that attribute explicitly specified.

That PR seems to cause regressions on the CUDA platform. This PR/commit makes the changes in PR 181, to be applicable for HIP only
2020-08-20 00:29:57 +00:00