part of the class signature is lost due to a problem with forward
declarations. The problem is probably caused by doxygen bug #7689.
It is confirmed to be fixed in doxygen >= 1.8.19.
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.
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`.
This fixes some gcc warnings such as:
```
Eigen/src/Core/GenericPacketMath.h:655:63: warning: implicit conversion turns floating-point number into bool: 'typename __gnu_cxx::__enable_if<__is_integer<bool>::__value, double>::__type' (aka 'double') to 'bool' [-Wimplicit-conversion-floating-point-to-bool]
Packet psqrt(const Packet& a) { EIGEN_USING_STD(sqrt); return sqrt(a); }
```
Details:
- Added `scalar_sqrt_op<bool>` (`-Wimplicit-conversion-floating-point-to-bool`).
- Added `scalar_square_op<bool>` and `scalar_cube_op<bool>`
specializations (`-Wint-in-bool-context`)
- Deprecated above specialized ops for bool.
- Modified `cxx11_tensor_block_eval` to specialize generator for
booleans (`-Wint-in-bool-context`) and to use `abs` instead of `square` to
avoid deprecated bool 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).
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`.
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`.
Missing inline breaks blas, since symbol generated in
`complex_single.cpp`, `complex_double.cpp`, `single.cpp`, `double.cpp`
Changed rest of inlines to `EIGEN_STRONG_INLINE`.
Both, Eigen::half and Eigen::Bfloat16 are implicitly convertible to
float and can hence be converted to bool via the conversion chain
Eigen::{half,bfloat16} -> float -> bool
We thus remove the explicit cast operator to bool.
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
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.
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.
Note that HTTPS must be used against the MathJax CDN when hosted on `eigen.tuxfamily.org` (which uses HTTPS) in order to avoid `Mixed Content`-errors from browsers. Using HTTPS for MathJax also works if the Eigen docs are hosted on plain HTTP.
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.
The `OpenGLSupport` module contains mostly deprecated features, and the
test is highly GL context-dependent, relies on deprecated GLUT, and
requires a display. Until the module is updated to support modern
OpenGL and the test to use newer windowing frameworks (e.g. GLFW)
it's probably best to disable the test by default.
The test can be enabled with `cmake -DEIGEN_TEST_OPENGL=ON`.
See #2053 for more details.
The existing test fails on several systems due to GL runtime version mismatches,
the use of deprecated features, and memory errors due to improper use of GLUT.
The test was modified to:
- Run within a display function, allowing proper GLUT cleanup.
- Generate dynamic shaders with a supported GLSL version string and output variables.
- Report shader compilation errors.
- Check GL context version before launching version-specific tests.
Note that most of the existing `OpenGLSupport` module and tests rely on deprecated
features (e.g. fixed-function pipeline). The test was modified to allow it to
pass on various systems. We might want to consider removing the module or re-writing
it entirely to support modern OpenGL. This is beyond the scope of this patch.
Testing of legacy GL (for platforms that support it) can be enabled by defining
`EIGEN_LEGACY_OPENGL`. Otherwise, the test will try to create a modern context.
Tested on
- MacBook Air (2019), macOS Catalina 10.15.7 (OpenGL 2.1, 4.1)
- Debian 10.6, NVidia Quadro K1200 (OpenGL 3.1, 3.3)
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.
The following commit breaks Eigen for ROCm (and probably CUDA too) with the following error
e265f7ed8e
```
Building HIPCC object test/CMakeFiles/gpu_basic.dir/gpu_basic_generated_gpu_basic.cu.o
In file included from /home/rocm-user/eigen/test/gpu_basic.cu:20:
In file included from /home/rocm-user/eigen/test/main.h:355:
In file included from /home/rocm-user/eigen/Eigen/QR:11:
In file included from /home/rocm-user/eigen/Eigen/Core:169:
/home/rocm-user/eigen/Eigen/src/Core/arch/Default/Half.h:825:76: error: use of undeclared identifier 'numext'; did you mean 'Eigen::numext'?
return Eigen::half_impl::raw_uint16_to_half(__ldg(reinterpret_cast<const numext::uint16_t*>(ptr)));
^~~~~~
Eigen::numext
/home/rocm-user/eigen/Eigen/src/Core/MathFunctions.h:968:11: note: 'Eigen::numext' declared here
namespace numext {
^
1 error generated when compiling for gfx900.
CMake Error at gpu_basic_generated_gpu_basic.cu.o.cmake:192 (message):
Error generating file
/home/rocm-user/eigen/build/test/CMakeFiles/gpu_basic.dir//./gpu_basic_generated_gpu_basic.cu.o
test/CMakeFiles/gpu_basic.dir/build.make:63: recipe for target 'test/CMakeFiles/gpu_basic.dir/gpu_basic_generated_gpu_basic.cu.o' failed
make[3]: *** [test/CMakeFiles/gpu_basic.dir/gpu_basic_generated_gpu_basic.cu.o] Error 1
CMakeFiles/Makefile2:16611: recipe for target 'test/CMakeFiles/gpu_basic.dir/all' failed
make[2]: *** [test/CMakeFiles/gpu_basic.dir/all] Error 2
CMakeFiles/Makefile2:16618: recipe for target 'test/CMakeFiles/gpu_basic.dir/rule' failed
make[1]: *** [test/CMakeFiles/gpu_basic.dir/rule] Error 2
Makefile:5401: recipe for target 'gpu_basic' failed
make: *** [gpu_basic] Error 2
```
The fix is in this commit is trivial. Please review and merge
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.
