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Add a specialization of Eigen::numext::conj for std::complex<T> to be used when compiling a cuda kernel. This fixes the compilation of TensorFlow 1.4 with clang 6.0 used as CUDA compiler with libc++.

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This follows the previous change in 2a69290ddb
, which mentions OSX (I guess because it uses libc++ too).
This commit is contained in:
nicolov 2018-04-13 22:29:10 +00:00
parent 775766d175
commit 39c2cba810
1 changed files with 16 additions and 2 deletions
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18
Eigen/src/Core/MathFunctions.h
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@ -238,7 +238,7 @@ struct imag_ref_retval
****************************************************************************/
template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct conj_impl
struct conj_default_impl
{
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x)
@ -248,7 +248,7 @@ struct conj_impl
};
template<typename Scalar>
struct conj_impl<Scalar,true>
struct conj_default_impl<Scalar,true>
{
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x)
@ -258,6 +258,20 @@ struct conj_impl<Scalar,true>
}
};
template<typename Scalar> struct conj_impl : conj_default_impl<Scalar> {};
#ifdef EIGEN_CUDA_ARCH
template<typename T>
struct conj_impl<std::complex<T> >
{
EIGEN_DEVICE_FUNC
static inline std::complex<T> run(const std::complex<T>& x)
{
return std::complex<T>(x.real(), -x.imag());
}
};
#endif
template<typename Scalar>
struct conj_retval
{