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.
The following commit causes regressions in the ROCm/HIP support for Eigen
e55182ac09
I suspect the same breakages occur on the CUDA side too.
The above commit puts the EIGEN_CONSTEXPR attribute on `half_base` constructor. `half_base` is derived from `__half_raw`.
When compiling with GPU support, the definition of `__half_raw` gets picked up from the GPU Compiler specific header files (`hip_fp16.h`, `cuda_fp16.h`). Properly supporting the above commit would require adding the `constexpr` attribute to the `__half_raw` constructor (and other `*half*` routines) in those header files. While that is something we can explore in the future, for now we need to undo the above commit when compiling with GPU support, which is what this commit does.
This commit also reverts a small change in the `raw_uint16_to_half` routine made by the above commit. Similar to the case above, that change was leading to compile errors due to the fact that `__half_raw` has a different definition when compiling with DPU support.
CastXML simulates the preprocessors of other compilers, but actually
parses the translation unit with an internal Clang compiler.
Use the same `vld1q_u64` workaround that we do for Clang.
Fixes: #1979
Implemented fast size-4 matrix inverse (mimicking Inverse_SSE.h) using NEON intrinsics.
```
Benchmark Time CPU Time Old Time New CPU Old CPU New
--------------------------------------------------------------------------------------------------------
BM_float -0.1285 -0.1275 568 495 572 499
BM_double -0.2265 -0.2254 638 494 641 496
```
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
Some platforms define int64_t to be long long even for C++03. If this is
the case we miss the definition of internal::make_unsigned for this
type. If we just define the template we get duplicated definitions
errors for platforms defining int64_t as signed long for C++03.
We need to find a way to distinguish both cases at compile-time.
The NEON implementation mimics the SSE implementation, but didn't mention the caveat that due to the unsigned of signed integer conversions, not all values in the original floating point represented are supported.
If we have explicit conversion operators available (C++11) we define
explicit casts from bfloat16 to other types. If not (C++03), we don't
define conversion operators but rely on implicit conversion chains from
bfloat16 over float to other types.
Specialized `bfloat16_impl::float_to_bfloat16_rtne(float)` for normal floating point numbers, infinity and zero, in order to improve the performance of `bfloat16::bfloat16(const T&)` for integer argument types.
A reduction of more than 20% of the runtime duration of conversion from int to bfloat16 was observed, using Visual C++ 2019 on Windows 10.
Conversion from `bfloat16` to `float` and `double` is lossless. It seems natural to allow the conversion to be implicit, as the C++ language also support implicit conversion from a smaller to a larger floating point type.
Intel's OneDLL bfloat16 implementation also has an implicit `operator float()`: https://github.com/oneapi-src/oneDNN/blob/v1.5/src/common/bfloat16.hpp
- Guard fundamental types that are not available pre C++11
- Separate subsequent angle brackets >> by spaces
- Allow casting of Eigen::half and Eigen::bfloat16 to complex types
The original tensor casts were only defined for
`SrcCoeffRatio`:`TgtCoeffRatio` 1:1, 1:2, 2:1, 4:1. Here we add the
missing 1:N and 8:1.
We also add casting `Eigen::half` to/from `std::complex<T>`, which
was missing to make it consistent with `Eigen:bfloat16`, and
generalize the overload to work for any complex type.
Tests were added to `basicstuff`, `packetmath`, and
`cxx11_tensor_casts` to test all cast configurations.
Added missing `pmadd<Packet2f>` for NEON. This leads to significant
improvement in precision than previous `pmul+padd`, which was causing
the `pcos` tests to fail. Also added an approx test with
`std::sin`/`std::cos` since otherwise returning any `a^2+b^2=1` would
pass.
Modified `log(denorm)` tests. Denorms are not always supported by all
systems (returns `::min`), are always flushed to zero on 32-bit arm,
and configurably flush to zero on sse/avx/aarch64. This leads to
inconsistent results across different systems (i.e. `-inf` vs `nan`).
Added a check for existence and exclude ARM.
Removed logistic exactness test, since scalar and vectorized versions
follow different code-paths due to differences in `pexp` and `pmadd`,
which result in slightly different values. For example, exactness always
fails on arm, aarch64, and altivec.
The NEON `pcast` operators are all implemented and tested for existing
packets. This requires adding a `pcast(a,b,c,d,e,f,g,h)` for casting
between `int64_t` and `int8_t` in `GenericPacketMath.h`.
Removed incorrect `HasHalfPacket` definition for NEON's
`Packet2l`/`Packet2ul`.
Adjustments were also made to the `packetmath` tests. These include
- minor bug fixes for cast tests (i.e. 4:1 casts, only casting for
packets that are vectorizable)
- added 8:1 cast tests
- random number generation
- original had uninteresting 0 to 0 casts for many casts between
floating-point and integers, and exhibited signed overflow
undefined behavior
Tested:
```
$ aarch64-linux-gnu-g++ -static -I./ '-DEIGEN_TEST_PART_ALL=1' test/packetmath.cpp -o packetmath
$ adb push packetmath /data/local/tmp/
$ adb shell "/data/local/tmp/packetmath"
```
The use of the `packet_traits<>::HasCast` field is currently inconsistent with
`type_casting_traits<>`, and is unused apart from within
`test/packetmath.cpp`. In addition, those packetmath cast tests do not
currently reflect how casts are performed in practice: they ignore the
`SrcCoeffRatio` and `TgtCoeffRatio` fields, assuming a 1:1 ratio.
Here we remove the unsed `HasCast`, and modify the packet cast tests to
better reflect their usage.
- Use standard types in SYCL/PacketMath.h to avoid compilation problems on Windows
- Add EIGEN_HAS_CONSTEXPR to cxx11_tensor_argmax_sycl.cpp to fix build problems on Windows
This PR tries to fix an incorrect usage of `if defined(EIGEN_ARCH_PPC)`
in `Eigen/Core` header.
In `Eigen/src/Core/util/Macros.h`, EIGEN_ARCH_PPC was explicitly defined
as either 0 or 1. As a result `if defined(EIGEN_ARCH_PPC)` will always be true.
This causes issues when building on non PPC platform and `MatrixProduct.h` is not
available.
This fix changes `if defined(EIGEN_ARCH_PPC)` => `if EIGEN_ARCH_PPC`.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This change also contains a few minor cleanups:
1. Remove packet op pnot, which is not needed for anything other than pcmp_le_or_nan,
which can be done in other ways.
2. Remove the "HasInsert" enum, which is no longer needed since we removed the
corresponding packet ops.
3. Add faster pselect op for Packet4i when SSE4.1 is supported.
Among other things, this makes the fast transposeInPlace() method available for Matrix<bool>.
Run on ************** (72 X 2994 MHz CPUs); 2020-05-09T10:51:02.372347913-07:00
CPU: Intel Skylake Xeon with HyperThreading (36 cores) dL1:32KB dL2:1024KB dL3:24MB
Benchmark Time(ns) CPU(ns) Iterations
-----------------------------------------------------------------------
BM_TransposeInPlace<float>/4 9.77 9.77 71670320
BM_TransposeInPlace<float>/8 21.9 21.9 31929525
BM_TransposeInPlace<float>/16 66.6 66.6 10000000
BM_TransposeInPlace<float>/32 243 243 2879561
BM_TransposeInPlace<float>/59 844 844 829767
BM_TransposeInPlace<float>/64 933 933 750567
BM_TransposeInPlace<float>/128 3944 3945 177405
BM_TransposeInPlace<float>/256 16853 16853 41457
BM_TransposeInPlace<float>/512 204952 204968 3448
BM_TransposeInPlace<float>/1k 1053889 1053861 664
BM_TransposeInPlace<bool>/4 14.4 14.4 48637301
BM_TransposeInPlace<bool>/8 36.0 36.0 19370222
BM_TransposeInPlace<bool>/16 31.5 31.5 22178902
BM_TransposeInPlace<bool>/32 111 111 6272048
BM_TransposeInPlace<bool>/59 626 626 1000000
BM_TransposeInPlace<bool>/64 428 428 1632689
BM_TransposeInPlace<bool>/128 1677 1677 417377
BM_TransposeInPlace<bool>/256 7126 7126 96264
BM_TransposeInPlace<bool>/512 29021 29024 24165
BM_TransposeInPlace<bool>/1k 116321 116330 6068
This commit applies the following changes:
- Moving the `scamLauncher` specialization inside internal namespace to fix compiler crash on TensorScan for SYCL backend.
- Replacing `SYCL/sycl.hpp` to `CL/sycl.hpp` in order to follow SYCL 1.2.1 standard.
- minor fixes: commenting out an unused variable to avoid compiler warnings.
Some architectures have no convinient way to determine cache sizes at
runtime. Eigen's GEBP kernel falls back to default cache values in this
case which might not be correct in all situations.
This patch introduces three preprocessor directives
`EIGEN_DEFAULT_L1_CACHE_SIZE`
`EIGEN_DEFAULT_L2_CACHE_SIZE`
`EIGEN_DEFAULT_L3_CACHE_SIZE`
to give users the possibility to set these default values explicitly.
This will allow us to define multiple packet types backed by the same vector type, e.g., __m128i.
Use this machanism to define packets for half and clean up the packet op implementations.
{uint8, int8} -> {int16, uint16, int32, uint32, float}
{uint16, int16} -> {int32, uint32, int64, uint64, float}
for NEON. These conversions were advertised as vectorized, but not actually implemented.
commainitialier unit-test never actually called `test_block_recursion`, which also was not correctly implemented and would have caused too deep template recursion.
The removed `finished()` call was responsible for enforcing that the
initializer was provided the correct number of values. Putting it back in
to restore previous behavior.
The error generated by the compiler was:
no matching function for call to 'maxi'
RealScalar threshold = numext::maxi(tol*tol*rhsNorm2,considerAsZero);
The important part in the following notes was:
candidate template ignored: deduced conflicting
types for parameter 'T'"
('codi::Multiply11<...>' vs. 'codi::ActiveReal<...>')
EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
I am using CoDiPack to provide the RealScalar type.
This bug was introduced in bc000deaa Fix conjugate-gradient for very small rhs
- access violation when initializing 0x0 matrices
- exception can be thrown during stack unwind while comma-initializing a matrix if eigen_assert if configured to throw