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483 lines
16 KiB
C++
483 lines
16 KiB
C++
// Standard 16-bit float type, mostly useful for GPUs. Defines a new
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// class Eigen::half (inheriting from CUDA's __half struct) with
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// operator overloads such that it behaves basically as an arithmetic
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// type. It will be quite slow on CPUs (so it is recommended to stay
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// in fp32 for CPUs, except for simple parameter conversions, I/O
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// to disk and the likes), but fast on GPUs.
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//
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//
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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//
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// The conversion routines are Copyright (c) Fabian Giesen, 2016.
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// The original license follows:
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//
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// Copyright (c) Fabian Giesen, 2016
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// All rights reserved.
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted.
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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// “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#ifndef EIGEN_HALF_CUDA_H
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#define EIGEN_HALF_CUDA_H
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#if __cplusplus > 199711L
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#define EIGEN_EXPLICIT_CAST(tgt_type) explicit operator tgt_type()
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#else
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#define EIGEN_EXPLICIT_CAST(tgt_type) operator tgt_type()
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#endif
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#if !defined(EIGEN_HAS_CUDA_FP16)
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// Make our own __half definition that is similar to CUDA's.
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struct __half {
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unsigned short x;
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};
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#endif
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namespace Eigen {
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namespace internal {
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x);
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff);
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h);
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} // end namespace internal
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// Class definition.
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struct half : public __half {
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EIGEN_DEVICE_FUNC half() {}
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EIGEN_DEVICE_FUNC half(const __half& h) : __half(h) {}
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EIGEN_DEVICE_FUNC half(const half& h) : __half(h) {}
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explicit EIGEN_DEVICE_FUNC half(bool b)
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: __half(internal::raw_uint16_to_half(b ? 0x3c00 : 0)) {}
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explicit EIGEN_DEVICE_FUNC half(int i)
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: __half(internal::float_to_half_rtne(static_cast<float>(i))) {}
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explicit EIGEN_DEVICE_FUNC half(long l)
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: __half(internal::float_to_half_rtne(static_cast<float>(l))) {}
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explicit EIGEN_DEVICE_FUNC half(long long ll)
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: __half(internal::float_to_half_rtne(static_cast<float>(ll))) {}
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explicit EIGEN_DEVICE_FUNC half(float f)
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: __half(internal::float_to_half_rtne(f)) {}
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explicit EIGEN_DEVICE_FUNC half(double d)
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: __half(internal::float_to_half_rtne(static_cast<float>(d))) {}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(bool) const {
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// +0.0 and -0.0 become false, everything else becomes true.
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return (x & 0x7fff) != 0;
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(signed char) const {
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return static_cast<signed char>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned char) const {
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return static_cast<unsigned char>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(short) const {
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return static_cast<short>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned short) const {
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return static_cast<unsigned short>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(int) const {
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return static_cast<int>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned int) const {
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return static_cast<unsigned int>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(long) const {
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return static_cast<long>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned long) const {
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return static_cast<unsigned long>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(long long) const {
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return static_cast<long long>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned long long) const {
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return static_cast<unsigned long long>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(float) const {
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return internal::half_to_float(*this);
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}
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EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(double) const {
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return static_cast<double>(internal::half_to_float(*this));
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}
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EIGEN_DEVICE_FUNC half& operator=(const half& other) {
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x = other.x;
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return *this;
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}
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};
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#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
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// Intrinsics for native fp16 support. Note that on current hardware,
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// these are no faster than fp32 arithmetic (you need to use the half2
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// versions to get the ALU speed increased), but you do save the
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// conversion steps back and forth.
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__device__ half operator + (const half& a, const half& b) {
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return __hadd(a, b);
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}
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__device__ half operator * (const half& a, const half& b) {
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return __hmul(a, b);
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}
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__device__ half operator - (const half& a, const half& b) {
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return __hsub(a, b);
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}
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__device__ half operator / (const half& a, const half& b) {
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float num = __half2float(a);
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float denom = __half2float(b);
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return __float2half(num / denom);
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}
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__device__ half operator - (const half& a) {
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return __hneg(a);
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}
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__device__ half& operator += (half& a, const half& b) {
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a = a + b;
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return a;
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}
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__device__ half& operator *= (half& a, const half& b) {
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a = a * b;
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return a;
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}
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__device__ half& operator -= (half& a, const half& b) {
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a = a - b;
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return a;
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}
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__device__ half& operator /= (half& a, const half& b) {
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a = a / b;
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return a;
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}
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__device__ bool operator == (const half& a, const half& b) {
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return __heq(a, b);
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}
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__device__ bool operator != (const half& a, const half& b) {
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return __hne(a, b);
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}
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__device__ bool operator < (const half& a, const half& b) {
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return __hlt(a, b);
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}
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__device__ bool operator <= (const half& a, const half& b) {
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return __hle(a, b);
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}
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__device__ bool operator > (const half& a, const half& b) {
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return __hgt(a, b);
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}
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__device__ bool operator >= (const half& a, const half& b) {
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return __hge(a, b);
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}
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#else // Emulate support for half floats
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// Definitions for CPUs and older CUDA, mostly working through conversion
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// to/from fp32.
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator + (const half& a, const half& b) {
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return half(float(a) + float(b));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator * (const half& a, const half& b) {
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return half(float(a) * float(b));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator - (const half& a, const half& b) {
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return half(float(a) - float(b));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator / (const half& a, const half& b) {
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return half(float(a) / float(b));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator - (const half& a) {
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half result;
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result.x = a.x ^ 0x8000;
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return result;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator += (half& a, const half& b) {
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a = half(float(a) + float(b));
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return a;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator *= (half& a, const half& b) {
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a = half(float(a) * float(b));
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return a;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator -= (half& a, const half& b) {
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a = half(float(a) - float(b));
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return a;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator /= (half& a, const half& b) {
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a = half(float(a) / float(b));
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return a;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator == (const half& a, const half& b) {
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return float(a) == float(b);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator != (const half& a, const half& b) {
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return float(a) != float(b);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator < (const half& a, const half& b) {
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return float(a) < float(b);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator <= (const half& a, const half& b) {
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return float(a) <= float(b);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator > (const half& a, const half& b) {
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return float(a) > float(b);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator >= (const half& a, const half& b) {
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return float(a) >= float(b);
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}
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#endif // Emulate support for half floats
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// Division by an index. Do it in full float precision to avoid accuracy
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// issues in converting the denominator to half.
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator / (const half& a, Index b) {
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return Eigen::half(static_cast<float>(a) / static_cast<float>(b));
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}
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// Conversion routines, including fallbacks for the host or older CUDA.
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// Note that newer Intel CPUs (Haswell or newer) have vectorized versions of
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// these in hardware. If we need more performance on older/other CPUs, they are
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// also possible to vectorize directly.
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namespace internal {
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x) {
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__half h;
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h.x = x;
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return h;
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}
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union FP32 {
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unsigned int u;
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float f;
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};
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff) {
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#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
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return __float2half(ff);
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#elif defined(EIGEN_HAS_FP16_C)
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__half h;
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h.x = _cvtss_sh(ff, 0);
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return h;
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#else
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FP32 f; f.f = ff;
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const FP32 f32infty = { 255 << 23 };
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const FP32 f16max = { (127 + 16) << 23 };
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const FP32 denorm_magic = { ((127 - 15) + (23 - 10) + 1) << 23 };
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unsigned int sign_mask = 0x80000000u;
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__half o = { 0 };
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unsigned int sign = f.u & sign_mask;
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f.u ^= sign;
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// NOTE all the integer compares in this function can be safely
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// compiled into signed compares since all operands are below
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// 0x80000000. Important if you want fast straight SSE2 code
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// (since there's no unsigned PCMPGTD).
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if (f.u >= f16max.u) { // result is Inf or NaN (all exponent bits set)
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o.x = (f.u > f32infty.u) ? 0x7e00 : 0x7c00; // NaN->qNaN and Inf->Inf
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} else { // (De)normalized number or zero
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if (f.u < (113 << 23)) { // resulting FP16 is subnormal or zero
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// use a magic value to align our 10 mantissa bits at the bottom of
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// the float. as long as FP addition is round-to-nearest-even this
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// just works.
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f.f += denorm_magic.f;
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// and one integer subtract of the bias later, we have our final float!
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o.x = static_cast<unsigned short>(f.u - denorm_magic.u);
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} else {
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unsigned int mant_odd = (f.u >> 13) & 1; // resulting mantissa is odd
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// update exponent, rounding bias part 1
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f.u += ((unsigned int)(15 - 127) << 23) + 0xfff;
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// rounding bias part 2
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f.u += mant_odd;
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// take the bits!
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o.x = static_cast<unsigned short>(f.u >> 13);
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}
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}
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o.x |= static_cast<unsigned short>(sign >> 16);
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return o;
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#endif
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h) {
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#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
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return __half2float(h);
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#elif defined(EIGEN_HAS_FP16_C)
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return _cvtsh_ss(h.x);
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#else
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const FP32 magic = { 113 << 23 };
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const unsigned int shifted_exp = 0x7c00 << 13; // exponent mask after shift
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FP32 o;
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o.u = (h.x & 0x7fff) << 13; // exponent/mantissa bits
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unsigned int exp = shifted_exp & o.u; // just the exponent
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o.u += (127 - 15) << 23; // exponent adjust
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// handle exponent special cases
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if (exp == shifted_exp) { // Inf/NaN?
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o.u += (128 - 16) << 23; // extra exp adjust
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} else if (exp == 0) { // Zero/Denormal?
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o.u += 1 << 23; // extra exp adjust
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o.f -= magic.f; // renormalize
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}
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o.u |= (h.x & 0x8000) << 16; // sign bit
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return o.f;
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#endif
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}
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} // end namespace internal
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// Traits.
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namespace internal {
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template<> struct is_arithmetic<half> { enum { value = true }; };
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} // end namespace internal
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template<> struct NumTraits<Eigen::half>
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: GenericNumTraits<Eigen::half>
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{
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EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE float dummy_precision() { return 1e-3f; }
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EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half highest() {
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return internal::raw_uint16_to_half(0x7bff);
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}
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EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half lowest() {
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return internal::raw_uint16_to_half(0xfbff);
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}
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};
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// Infinity/NaN checks.
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namespace numext {
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isinf)(const Eigen::half& a) {
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return (a.x & 0x7fff) == 0x7c00;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isnan)(const Eigen::half& a) {
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#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
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return __hisnan(a);
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#else
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return (a.x & 0x7fff) > 0x7c00;
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#endif
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isfinite)(const Eigen::half& a) {
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return !(Eigen::numext::isinf)(a) && !(Eigen::numext::isnan)(a);
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half abs(const Eigen::half& a) {
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Eigen::half result;
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result.x = a.x & 0x7FFF;
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return result;
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half exp(const Eigen::half& a) {
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return Eigen::half(::expf(float(a)));
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half log(const Eigen::half& a) {
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return Eigen::half(::logf(float(a)));
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half sqrt(const Eigen::half& a) {
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return Eigen::half(::sqrtf(float(a)));
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half floor(const Eigen::half& a) {
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return Eigen::half(::floorf(float(a)));
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}
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template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half ceil(const Eigen::half& a) {
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return Eigen::half(::ceilf(float(a)));
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}
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} // end namespace numext
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} // end namespace Eigen
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// Standard mathematical functions and trancendentals.
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half fabsh(const Eigen::half& a) {
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Eigen::half result;
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result.x = a.x & 0x7FFF;
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return result;
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half exph(const Eigen::half& a) {
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return Eigen::half(::expf(float(a)));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half logh(const Eigen::half& a) {
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return Eigen::half(::logf(float(a)));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half sqrth(const Eigen::half& a) {
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return Eigen::half(::sqrtf(float(a)));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half floorh(const Eigen::half& a) {
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return Eigen::half(::floorf(float(a)));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half ceilh(const Eigen::half& a) {
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return Eigen::half(::ceilf(float(a)));
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC int (isnan)(const Eigen::half& a) {
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return (Eigen::numext::isnan)(a);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC int (isinf)(const Eigen::half& a) {
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return (Eigen::numext::isinf)(a);
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}
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC int (isfinite)(const Eigen::half& a) {
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return !(Eigen::numext::isinf)(a) && !(Eigen::numext::isnan)(a);
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}
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namespace std {
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#if __cplusplus > 199711L
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template <>
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struct hash<Eigen::half> {
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t operator()(const Eigen::half& a) const {
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return static_cast<std::size_t>(a.x);
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}
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};
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#endif
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} // end namespace std
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// Add the missing shfl_xor intrinsic
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#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
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__device__ EIGEN_STRONG_INLINE Eigen::half __shfl_xor(Eigen::half var, int laneMask, int width=warpSize) {
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return static_cast<Eigen::half>(__shfl_xor(static_cast<float>(var), laneMask, width));
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}
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#endif
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// ldg() has an overload for __half, but we also need one for Eigen::half.
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#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 320
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static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half __ldg(const Eigen::half* ptr) {
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return Eigen::internal::raw_uint16_to_half(
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__ldg(reinterpret_cast<const unsigned short*>(ptr)));
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}
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#endif
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#endif // EIGEN_HALF_CUDA_H
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