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* Augment NumTraits with min/max_exponent() again.Gravatar Antonio Sanchez2021-03-16
| | | | | | | | | | | | 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
* Revert "Augment NumTraits with min/max_exponent()."Gravatar David Tellenbach2021-03-17
| | | | This reverts commit 75ce9cd2a7aefaaea8543e2db14ce4dc149eeb03.
* Augment NumTraits with min/max_exponent().Gravatar Antonio Sanchez2021-03-17
| | | | | | | | 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
* Make half/bfloat16 constructor take inputs by value, fix powerpc test.Gravatar Antonio Sanchez2021-02-27
| | | | | | | | | | | | 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.
* Make it possible to specify NaN propagation strategy for maxCoeff/minCoeff ↵Gravatar Rasmus Munk Larsen2021-02-24
| | | | reductions.
* New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps ↵Gravatar Rasmus Munk Larsen2021-02-17
| | | | for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
* Add more tests for pow and fix a corner case for huge exponent where the ↵Gravatar Rasmus Munk Larsen2021-02-05
| | | | result is always zero or infinite unless x is one.
* Eliminate implicit conversion warning in test/array_cwise.cppGravatar Antonio Sanchez2021-01-23
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* Replace std::isnan with numext::isnan for c++03Gravatar Antonio Sanchez2021-01-23
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* Fix pow and other cwise ops for half/bfloat16.Gravatar Antonio Sanchez2021-01-22
| | | | | | | | | | | | | 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.
* Vectorize `pow(x, y)`. This closes ↵Gravatar Rasmus Munk Larsen2021-01-18
| | | | | | | | | | | | | | | | | | | | | | 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.
* Add log2() to Eigen.Gravatar Rasmus Munk Larsen2020-12-04
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* Revert "Add log2() operator to Eigen"Gravatar Rasmus Munk Larsen2020-12-03
| | | | This reverts commit 4d91519a9be061da5d300079fca17dd0b9328050.
* Add log2() operator to EigenGravatar Rasmus Munk Larsen2020-12-03
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* Change the sign operator in Eigen to return NaN for NaN arguments, not zero.Gravatar Rasmus Munk Larsen2020-07-07
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* Make size odd for transposeInPlace test to make sure we hit the scalar path.Gravatar Rasmus Munk Larsen2020-05-07
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* Block transposeInPlace() when the matrix is real and square. This yields a ↵Gravatar Rasmus Munk Larsen2020-04-28
| | | | | | | | | | | | | | | | | | | | large speedup because we transpose in registers (or L1 if we spill), instead of one packet at a time, which in the worst case makes the code write to the same cache line PacketSize times instead of once. rmlarsen@rmlarsen4:.../eigen_bench/google3$ benchy --benchmarks=.*TransposeInPlace.*float.* --reference=srcfs experimental/users/rmlarsen/bench:matmul_bench 10 / 10 [====================================================================================================================================================================================================================] 100.00% 2m50s (Generated by http://go/benchy. Settings: --runs 5 --benchtime 1s --reference "srcfs" --benchmarks ".*TransposeInPlace.*float.*" experimental/users/rmlarsen/bench:matmul_bench) name old time/op new time/op delta BM_TransposeInPlace<float>/4 9.84ns ± 0% 6.51ns ± 0% -33.80% (p=0.008 n=5+5) BM_TransposeInPlace<float>/8 23.6ns ± 1% 17.6ns ± 0% -25.26% (p=0.016 n=5+4) BM_TransposeInPlace<float>/16 78.8ns ± 0% 60.3ns ± 0% -23.50% (p=0.029 n=4+4) BM_TransposeInPlace<float>/32 302ns ± 0% 229ns ± 0% -24.40% (p=0.008 n=5+5) BM_TransposeInPlace<float>/59 1.03µs ± 0% 0.84µs ± 1% -17.87% (p=0.016 n=5+4) BM_TransposeInPlace<float>/64 1.20µs ± 0% 0.89µs ± 1% -25.81% (p=0.008 n=5+5) BM_TransposeInPlace<float>/128 8.96µs ± 0% 3.82µs ± 2% -57.33% (p=0.008 n=5+5) BM_TransposeInPlace<float>/256 152µs ± 3% 17µs ± 2% -89.06% (p=0.008 n=5+5) BM_TransposeInPlace<float>/512 837µs ± 1% 208µs ± 0% -75.15% (p=0.008 n=5+5) BM_TransposeInPlace<float>/1k 4.28ms ± 2% 1.08ms ± 2% -74.72% (p=0.008 n=5+5)
* Add absolute_difference coefficient-wise binary Array functionGravatar Joel Holdsworth2020-03-19
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* Bug #1785: Introduce numext::rint.Gravatar Ilya Tokar2020-01-07
| | | | | | This provides a new op that matches std::rint and previous behavior of pround. Also adds corresponding unsupported/../Tensor op. Performance is the same as e. g. floor (tested SSE/AVX).
* Fix implementation of complex expm1. Add tests that fail with previous ↵Gravatar Srinivas Vasudevan2019-12-12
| | | | implementation, but pass with the current one.
* PR 719: fix real/imag namespace conflictGravatar Gael Guennebaud2019-10-08
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* Add more extensive tests of Array ctors, including {} variantsGravatar Gael Guennebaud2019-01-22
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* Add support for inverse hyperbolic functions.Gravatar Rasmus Munk Larsen2019-01-11
| | | | Fix cost of division.
* Rename test/array.cpp to test/array_cwise.cpp to avoid conflicts with the ↵Gravatar Gael Guennebaud2018-09-20
array header.
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