An analogue of `std::tuple` that works on device.
Context: I've tried `std::tuple` in various versions of NVCC and clang,
and although code seems to compile, it often fails to run - generating
"illegal memory access" errors, or "illegal instruction" errors.
This replacement does work on device.
MinGW spits out version strings like: `x86_64-w64-mingw32-g++ (GCC)
10-win32 20210110`, which causes the version extraction to fail.
Added support for this with tests.
Also added `make_unsigned` for `long long`, since mingw seems to
use that for `uint64_t`.
Related to #2268. CMake and build passes for me after this.
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`).
The `std::result_of` meta struct is deprecated in C++17 and removed
in C++20. It was still slipping through due to a faulty definition of
`EIGEN_HAS_STD_RESULT_OF`.
Added a new macro `EIGEN_HAS_STD_INVOKE_RESULT` and
`Eigen::internal::invoke_result` implementation with fallback for
pre C++17.
Replaces the `result_of` definition with one based on `std::invoke_result`
for C++17 and higher.
For completeness, added nullary op support for c++03.
Fixes#1850.
macOS defines int64_t as long long even for C++03 and therefore expects
a template specialization
internal::make_unsigned<long long>,
for C++03. Since other platforms define int64_t as long for C++03 we
cannot add the specialization for all cases.
Originating from
[this SO issue](https://stackoverflow.com/questions/65901014/how-to-solve-this-all-error-2-in-this-case),
some win32 compilers define `__int32` as a `long`, but MinGW defines
`std::int32_t` as an `int`, leading to a type conflict.
To avoid this, we remove the custom `typedef` definitions for win32. The
Tensor module requires C++11 anyways, so we are guaranteed to have
included `<cstdint>` already in `Eigen/Core`.
Also re-arranged the headers to only include `<cstdint>` in one place to
avoid this type of error again.
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.
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.
This makes both the small and huge argument cases faster because:
- for small inputs this removes the last pselect
- for large inputs only the reduction part follows a scalar path,
the rest use the same SIMD path as the small-argument case.
INFO: From Compiling tensorflow/core/kernels/maxpooling_op_gpu.cu.cc:
/b/f/w/run/external/eigen_archive/Eigen/src/Core/arch/GPU/Half.h(197): error: calling a __host__ function("std::equal_to<float> ::operator () const") from a __global__ function("tensorflow::_NV_ANON_NAMESPACE::MaxPoolGradBackwardNoMaskNHWC< ::Eigen::half> ") is not allowed
/b/f/w/run/external/eigen_archive/Eigen/src/Core/arch/GPU/Half.h(197): error: identifier "std::equal_to<float> ::operator () const" is undefined in device code"
/b/f/w/run/external/eigen_archive/Eigen/src/Core/arch/GPU/Half.h(197): error: calling a __host__ function("std::equal_to<float> ::operator () const") from a __global__ function("tensorflow::_NV_ANON_NAMESPACE::MaxPoolGradBackwardNoMaskNCHW< ::Eigen::half> ") is not allowed
/b/f/w/run/external/eigen_archive/Eigen/src/Core/arch/GPU/Half.h(197): error: identifier "std::equal_to<float> ::operator () const" is undefined in device code
4 errors detected in the compilation of "/tmp/tmpxft_00000011_00000000-6_maxpooling_op_gpu.cu.cpp1.ii".
ERROR: /tmpfs/tensor_flow/tensorflow/core/kernels/BUILD:3753:1: output 'tensorflow/core/kernels/_objs/pooling_ops_gpu/maxpooling_op_gpu.cu.pic.o' was not created
ERROR: /tmpfs/tensor_flow/tensorflow/core/kernels/BUILD:3753:1: Couldn't build file tensorflow/core/kernels/_objs/pooling_ops_gpu/maxpooling_op_gpu.cu.pic.o: not all outputs were created or valid
