Merged eigen/eigen into default

This commit is contained in:
Rasmus Larsen 2016-04-01 17:19:36 -07:00
commit 30242b7565
7 changed files with 67 additions and 12 deletions

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@ -42,7 +42,10 @@
#endif
#if defined(__CUDA_ARCH__)
// When compiling CUDA device code with NVCC, pull in math functions from the
// global namespace. In host mode, and when device doee with clang, use the
// std versions.
#if defined(__CUDA_ARCH__) && defined(__NVCC__)
#define EIGEN_USING_STD_MATH(FUNC) using ::FUNC;
#else
#define EIGEN_USING_STD_MATH(FUNC) using std::FUNC;

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@ -153,7 +153,9 @@ template<typename _Real> struct NumTraits<std::complex<_Real> >
MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
};
EIGEN_DEVICE_FUNC
static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
EIGEN_DEVICE_FUNC
static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
};
@ -177,7 +179,9 @@ struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
MulCost = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::MulCost
};
EIGEN_DEVICE_FUNC
static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
EIGEN_DEVICE_FUNC
static inline RealScalar dummy_precision() { return NumTraits<RealScalar>::dummy_precision(); }
};

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@ -341,6 +341,18 @@ template<> struct is_arithmetic<half> { enum { value = true }; };
} // end namespace internal
template<> struct NumTraits<Eigen::half>
: GenericNumTraits<Eigen::half>
{
EIGEN_DEVICE_FUNC static inline float dummy_precision() { return 1e-3f; }
EIGEN_DEVICE_FUNC static inline Eigen::half highest() {
return internal::raw_uint16_to_half(0x7bff);
}
EIGEN_DEVICE_FUNC static inline Eigen::half lowest() {
return internal::raw_uint16_to_half(0xfbff);
}
};
// Infinity/NaN checks.
namespace numext {
@ -348,7 +360,7 @@ namespace numext {
static inline EIGEN_DEVICE_FUNC bool (isinf)(const Eigen::half& a) {
return (a.x & 0x7fff) == 0x7c00;
}
static inline EIGEN_HALF_CUDA_H bool (isnan)(const Eigen::half& a) {
static inline EIGEN_DEVICE_FUNC bool (isnan)(const Eigen::half& a) {
#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hisnan(a);
#else
@ -403,6 +415,15 @@ using ::sqrt;
using ::floor;
using ::ceil;
#if __cplusplus > 199711L
template <>
struct hash<Eigen::half> {
size_t operator()(const Eigen::half& a) const {
return std::hash<unsigned short>()(a.x);
}
};
#endif
} // end namespace std
@ -411,7 +432,14 @@ using ::ceil;
__device__ inline Eigen::half __shfl_xor(Eigen::half var, int laneMask, int width=warpSize) {
return static_cast<Eigen::half>(__shfl_xor(static_cast<float>(var), laneMask, width));
}
#endif
// ldg() has an overload for __half, but we also need one for Eigen::half.
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 320
static inline EIGEN_DEVICE_FUNC Eigen::half __ldg(const Eigen::half* ptr) {
return Eigen::internal::raw_uint16_to_half(
__ldg(reinterpret_cast<const unsigned short*>(ptr)));
}
#endif

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@ -370,8 +370,8 @@
// Does the compiler support const expressions?
#ifdef __CUDACC__
// Const expressions are supported provided that c++11 is enabled and we're using nvcc 7.5 or above
#if defined(__CUDACC_VER__) && __CUDACC_VER__ >= 70500 && __cplusplus > 199711L
// Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above
#if __cplusplus > 199711L && defined(__CUDACC_VER__) && (defined(__clang__) || __CUDACC_VER__ >= 70500)
#define EIGEN_HAS_CONSTEXPR 1
#endif
#elif (defined(__cplusplus) && __cplusplus >= 201402L) || \

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@ -10,8 +10,9 @@
#ifndef EIGEN_CXX11_TENSOR_TENSOR_FFT_H
#define EIGEN_CXX11_TENSOR_TENSOR_FFT_H
// NVCC fails to compile this code
#if !defined(__CUDACC__)
// This code requires the ability to initialize arrays of constant
// values directly inside a class.
#if __cplusplus >= 201103L || EIGEN_COMP_MSVC >= 1900
namespace Eigen {
@ -564,7 +565,7 @@ struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, D
// This will support a maximum FFT size of 2^32 for each dimension
// m_sin_PI_div_n_LUT[i] = (-2) * std::sin(M_PI / std::pow(2,i)) ^ 2;
RealScalar m_sin_PI_div_n_LUT[32] = {
const RealScalar m_sin_PI_div_n_LUT[32] = {
RealScalar(0.0),
RealScalar(-2),
RealScalar(-0.999999999999999),
@ -600,7 +601,7 @@ struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, D
};
// m_minus_sin_2_PI_div_n_LUT[i] = -std::sin(2 * M_PI / std::pow(2,i));
RealScalar m_minus_sin_2_PI_div_n_LUT[32] = {
const RealScalar m_minus_sin_2_PI_div_n_LUT[32] = {
RealScalar(0.0),
RealScalar(0.0),
RealScalar(-1.00000000000000e+00),
@ -638,7 +639,7 @@ struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, D
} // end namespace Eigen
#endif // __CUDACC__
#endif // EIGEN_HAS_CONSTEXPR
#endif // EIGEN_CXX11_TENSOR_TENSOR_FFT_H

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@ -45,6 +45,23 @@ struct type2index {
}
};
template<DenseIndex n> struct NumTraits<type2index<n> >
{
typedef DenseIndex Real;
enum {
IsComplex = 0,
RequireInitialization = false,
ReadCost = 1,
AddCost = 1,
MulCost = 1
};
EIGEN_DEVICE_FUNC static inline Real epsilon() { return 0; }
EIGEN_DEVICE_FUNC static inline Real dummy_precision() { return 0; }
EIGEN_DEVICE_FUNC static inline Real highest() { return n; }
EIGEN_DEVICE_FUNC static inline Real lowest() { return n; }
};
namespace internal {
template <typename T>
EIGEN_DEVICE_FUNC void update_value(T& val, DenseIndex new_val) {

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@ -53,7 +53,9 @@ struct TensorUInt128
template<typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
explicit TensorUInt128(const T& x) : high(0), low(x) {
eigen_assert(x < NumTraits<LOW>::highest());
typedef typename conditional<sizeof(T) == 8, uint64_t, uint32_t>::type UnsignedT;
typedef typename conditional<sizeof(LOW) == 8, uint64_t, uint32_t>::type UnsignedLow;
eigen_assert(static_cast<UnsignedT>(x) <= static_cast<UnsignedLow>(NumTraits<LOW>::highest()));
eigen_assert(x >= 0);
}