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This fixes the problem with taking the address of temporary objects which clang11 treats as errors.
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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.
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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`).
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Previously was `int`. Brought up by Kyle Snow (Polaris Geospatial
Services) on the mailing list.
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The Eigen unit-tests started failing on the HIP/ROCm platform, after the following commit
https://gitlab.com/libeigen/eigen/-/commit/e7b8643d70dfbb02ad94186169a8f16041f05bc2
```
In file included from /home/rocm-user/eigen/test/main.h:360:
In file included from /home/rocm-user/eigen/Eigen/QR:11:
In file included from /home/rocm-user/eigen/Eigen/Core:162:
/home/rocm-user/eigen/Eigen/src/Core/util/Meta.h:300:17: error: constexpr function never produces a constant expression [-Winvalid-constexpr]
static float (max)() {
^
/home/rocm-user/eigen/Eigen/src/Core/util/Meta.h:304:12: note: non-constexpr function '__int_as_float' cannot be used in a constant expression
return HIPRT_MAX_NORMAL_F;
^
/home/rocm-user/eigen/Eigen/src/Core/arch/HIP/hcc/math_constants.h:14:28: note: expanded from macro 'HIPRT_MAX_NORMAL_F'
#define HIPRT_MAX_NORMAL_F __int_as_float(0x7f7fffff)
^
/opt/rocm/hip/include/hip/hcc_detail/device_functions.h:913:32: note: declared here
__device__ static inline float __int_as_float(int x) {
^
```
The problem seems to that some of the constants defined in the HIP `math_constants.h` have a call to `__int_as_float` routine which is not declared `constexpr` in the HIP runtime header file.
Working around this issue for now, be skipping the const_expr support (enabled via the above commit) on HIP
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innerStride(), outerStride(), and size()""
This reverts commit 5f0b4a4010af4cbf6161a0d1a03a747addc44a5d.
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This reverts commit f019b97aca82071f35726b1aaebf1c598770f0f5
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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
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This reverts commit 75ce9cd2a7aefaaea8543e2db14ce4dc149eeb03.
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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
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eigenvectors matrix is unitary.
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This is to support TensorFlow's `tf.math.floormod` for half.
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This is to resolve an issue for large inputs when +0.5 can
actually lead to +1 if the input doesn't have enough precision
to resolve the addition - leading to an off-by-one error.
See discussion on 9a663973.
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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
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This is for consistency with bfloat16, and to support initialization
with `std::iota`.
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Doesn't seem to correctly select the register type, and most types
lead to compiler crashes.
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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
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and _M_ARM64EC is not), and define EIGEN_ARCH_ARM64 for both the native ARM64 (_M_ARM64 is defined) or ARM64EC (_M_ARM64EC is defined). _M_ARM64EC is defined when the code is compiled by MSVC for ARM64EC, a new ARM64 ABI designed to be compatible with x64 application emulation on ARM64. If _M_ARM64EC is defined, _M_X64 and _M_AMD64 are also defined, so x64-specific code (especially intrinsics) is also compiled to ARM64 instructions (compliant with the ARM64EC ABI) for maximum x64 compatibility. Although a majority of x64-specific intrinsics can emulated by ARM64 instructions, it is still a good to simply recompile the native ARM64 code paths to ARM64EC for pure computation tasks, for performance reasons.
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Both CUDA and HIP require trivial default constructors for types used
in shared memory. Otherwise failing with
```
error: initialization is not supported for __shared__ variables.
```
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This was accidentally introduced when copying changes between repos.
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Currently, when compiling with HIP, Eigen::half is derived from the `__half_raw` struct that is defined within the hip_fp16.h header file. This is true for both the "host" compile phase and the "device" compile phase. This was causing a very hard to detect bug in the ROCm TensorFlow build.
In the ROCm Tensorflow build,
* files that do not contain ant GPU code get compiled via gcc, and
* files that contnain GPU code get compiled via hipcc.
In certain case, we have a function that is defined in a file that is compiled by hipcc, and is called in a file that is compiled by gcc. If such a function had Eigen::half has a "pass-by-value" argument, its value was getting corrupted, when received by the function.
The reason for this seems to be that for the gcc compile, Eigen::half is derived from a `__half_raw` struct that has `uint16_t` as the data-store, and for hipcc the `__half_raw` implementation uses `_Float16` as the data store. There is some ABI incompatibility between gcc / hipcc (which is essentially latest clang), which results in the Eigen::half value (which is correct at the call-site) getting randomly corrupted when passed to the function.
Changing the Eigen::half argument to be "pass by reference" seems to workaround the error.
In order to fix it such that we do not run into it again in TF, this commit changes the Eigne::half implementation to use the same `__half_raw` implementation as the non-GPU compile, during host compile phase of the hipcc compile.
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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
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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.
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innerStride(), outerStride(), and size()"
This reverts commit 6cbb3038ac48cb5fe17eba4dfbf26e3e798041f1 because it
breaks clang-10 builds on x86 and aarch64 when C++11 is enabled.
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outerStride(), and size()
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This reverts commit e72dfeb8b9fa5662831b5d0bb9d132521f9173dd
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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.
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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.
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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.
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float (or long to double)
(cherry picked from commit cd541ad52c8152340469cae210312c0e27829c8d)
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(cherry picked from commit 838f3d8ce22a5549ef10c7386fb03040721749a0)
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(cherry picked from commit 2883e91ce5a99c391fbf28e20160176b70854992)
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(cherry picked from commit c22c103e932e511e96645186831363585a44b7a3)
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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).
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Chip Kerchner
Rasmus Munk Larsen
Antonio Sanchez
Deven Desai
Steve Bronder
Christoph Hertzberg
David Tellenbach
Niek Bouman
Theo Fletcher
Ben Niu