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#pragma once
/// Defines the Half type (half-precision floating-point) including conversions
/// to standard C types and basic arithmetic operations. Note that arithmetic
/// operations are implemented by converting to floating point and
/// performing the operation in float32, instead of using CUDA half intrinisics.
/// Most uses of this type within ATen are memory bound, including the
/// element-wise kernels, and the half intrinisics aren't efficient on all GPUs.
/// If you are writing a compute bound kernel, you can use the CUDA half
/// intrinsics directly on the Half type from device code.
#include <c10/macros/Macros.h>
#include <c10/util/C++17.h>
#if defined(__cplusplus) && (__cplusplus >= 201103L)
#include <cmath>
#include <cstdint>
#elif !defined(__OPENCL_VERSION__)
#include <math.h>
#include <stdint.h>
#endif
#ifdef _MSC_VER
#include <intrin.h>
#endif
#include <complex>
#include <cstring>
#include <cstdint>
#include <iosfwd>
#include <limits>
#include <sstream>
#include <stdexcept>
#include <string>
#include <utility>
#ifdef __CUDACC__
#include <cuda_fp16.h>
#endif
#ifdef __HIPCC__
#include <hip/hip_fp16.h>
#endif
namespace c10 {
namespace detail {
inline float fp32_from_bits(uint32_t w) {
#if defined(__OPENCL_VERSION__)
return as_float(w);
#elif defined(__CUDA_ARCH__)
return __uint_as_float((unsigned int)w);
#elif defined(__INTEL_COMPILER)
return _castu32_f32(w);
#else
union {
uint32_t as_bits;
float as_value;
} fp32 = {w};
return fp32.as_value;
#endif
}
inline uint32_t fp32_to_bits(float f) {
#if defined(__OPENCL_VERSION__)
return as_uint(f);
#elif defined(__CUDA_ARCH__)
return (uint32_t)__float_as_uint(f);
#elif defined(__INTEL_COMPILER)
return _castf32_u32(f);
#else
union {
float as_value;
uint32_t as_bits;
} fp32 = {f};
return fp32.as_bits;
#endif
}
/*
* Convert a 16-bit floating-point number in IEEE half-precision format, in bit representation, to
* a 32-bit floating-point number in IEEE single-precision format, in bit representation.
*
* @note The implementation doesn't use any floating-point operations.
*/
inline uint32_t fp16_ieee_to_fp32_bits(uint16_t h) {
/*
* Extend the half-precision floating-point number to 32 bits and shift to the upper part of the 32-bit word:
* +---+-----+------------+-------------------+
* | S |EEEEE|MM MMMM MMMM|0000 0000 0000 0000|
* +---+-----+------------+-------------------+
* Bits 31 26-30 16-25 0-15
*
* S - sign bit, E - bits of the biased exponent, M - bits of the mantissa, 0 - zero bits.
*/
const uint32_t w = (uint32_t) h << 16;
/*
* Extract the sign of the input number into the high bit of the 32-bit word:
*
* +---+----------------------------------+
* | S |0000000 00000000 00000000 00000000|
* +---+----------------------------------+
* Bits 31 0-31
*/
const uint32_t sign = w & UINT32_C(0x80000000);
/*
* Extract mantissa and biased exponent of the input number into the bits 0-30 of the 32-bit word:
*
* +---+-----+------------+-------------------+
* | 0 |EEEEE|MM MMMM MMMM|0000 0000 0000 0000|
* +---+-----+------------+-------------------+
* Bits 30 27-31 17-26 0-16
*/
const uint32_t nonsign = w & UINT32_C(0x7FFFFFFF);
/*
* Renorm shift is the number of bits to shift mantissa left to make the half-precision number normalized.
* If the initial number is normalized, some of its high 6 bits (sign == 0 and 5-bit exponent) equals one.
* In this case renorm_shift == 0. If the number is denormalize, renorm_shift > 0. Note that if we shift
* denormalized nonsign by renorm_shift, the unit bit of mantissa will shift into exponent, turning the
* biased exponent into 1, and making mantissa normalized (i.e. without leading 1).
*/
#ifdef _MSC_VER
unsigned long nonsign_bsr;
_BitScanReverse(&nonsign_bsr, (unsigned long)nonsign);
uint32_t renorm_shift = (uint32_t)nonsign_bsr ^ 31;
#else
uint32_t renorm_shift = __builtin_clz(nonsign);
#endif
renorm_shift = renorm_shift > 5 ? renorm_shift - 5 : 0;
/*
* Iff half-precision number has exponent of 15, the addition overflows
* it into bit 31, and the subsequent shift turns the high 9 bits
* into 1. Thus inf_nan_mask == 0x7F800000 if the half-precision number
* had exponent of 15 (i.e. was NaN or infinity) 0x00000000 otherwise
*/
const int32_t inf_nan_mask =
((int32_t)(nonsign + 0x04000000) >> 8) & INT32_C(0x7F800000);
/*
* Iff nonsign is 0, it overflows into 0xFFFFFFFF, turning bit 31
* into 1. Otherwise, bit 31 remains 0. The signed shift right by 31
* broadcasts bit 31 into all bits of the zero_mask. Thus zero_mask ==
* 0xFFFFFFFF if the half-precision number was zero (+0.0h or -0.0h)
* 0x00000000 otherwise
*/
const int32_t zero_mask = (int32_t)(nonsign - 1) >> 31;
/*
* 1. Shift nonsign left by renorm_shift to normalize it (if the input
* was denormal)
* 2. Shift nonsign right by 3 so the exponent (5 bits originally)
* becomes an 8-bit field and 10-bit mantissa shifts into the 10 high
* bits of the 23-bit mantissa of IEEE single-precision number.
* 3. Add 0x70 to the exponent (starting at bit 23) to compensate the
* different in exponent bias (0x7F for single-precision number less 0xF
* for half-precision number).
* 4. Subtract renorm_shift from the exponent (starting at bit 23) to
* account for renormalization. As renorm_shift is less than 0x70, this
* can be combined with step 3.
* 5. Binary OR with inf_nan_mask to turn the exponent into 0xFF if the
* input was NaN or infinity.
* 6. Binary ANDNOT with zero_mask to turn the mantissa and exponent
* into zero if the input was zero.
* 7. Combine with the sign of the input number.
*/
return sign |
((((nonsign << renorm_shift >> 3) + ((0x70 - renorm_shift) << 23)) |
inf_nan_mask) &
~zero_mask);
}
/*
* Convert a 16-bit floating-point number in IEEE half-precision format, in bit representation, to
* a 32-bit floating-point number in IEEE single-precision format.
*
* @note The implementation relies on IEEE-like (no assumption about rounding mode and no operations on denormals)
* floating-point operations and bitcasts between integer and floating-point variables.
*/
inline float fp16_ieee_to_fp32_value(uint16_t h) {
/*
* Extend the half-precision floating-point number to 32 bits and shift to the upper part of the 32-bit word:
* +---+-----+------------+-------------------+
* | S |EEEEE|MM MMMM MMMM|0000 0000 0000 0000|
* +---+-----+------------+-------------------+
* Bits 31 26-30 16-25 0-15
*
* S - sign bit, E - bits of the biased exponent, M - bits of the mantissa, 0 - zero bits.
*/
const uint32_t w = (uint32_t) h << 16;
/*
* Extract the sign of the input number into the high bit of the 32-bit word:
*
* +---+----------------------------------+
* | S |0000000 00000000 00000000 00000000|
* +---+----------------------------------+
* Bits 31 0-31
*/
const uint32_t sign = w & UINT32_C(0x80000000);
/*
* Extract mantissa and biased exponent of the input number into the high bits of the 32-bit word:
*
* +-----+------------+---------------------+
* |EEEEE|MM MMMM MMMM|0 0000 0000 0000 0000|
* +-----+------------+---------------------+
* Bits 27-31 17-26 0-16
*/
const uint32_t two_w = w + w;
/*
* Shift mantissa and exponent into bits 23-28 and bits 13-22 so they become mantissa and exponent
* of a single-precision floating-point number:
*
* S|Exponent | Mantissa
* +-+---+-----+------------+----------------+
* |0|000|EEEEE|MM MMMM MMMM|0 0000 0000 0000|
* +-+---+-----+------------+----------------+
* Bits | 23-31 | 0-22
*
* Next, there are some adjustments to the exponent:
* - The exponent needs to be corrected by the difference in exponent bias between single-precision and half-precision
* formats (0x7F - 0xF = 0x70)
* - Inf and NaN values in the inputs should become Inf and NaN values after conversion to the single-precision number.
* Therefore, if the biased exponent of the half-precision input was 0x1F (max possible value), the biased exponent
* of the single-precision output must be 0xFF (max possible value). We do this correction in two steps:
* - First, we adjust the exponent by (0xFF - 0x1F) = 0xE0 (see exp_offset below) rather than by 0x70 suggested
* by the difference in the exponent bias (see above).
* - Then we multiply the single-precision result of exponent adjustment by 2**(-112) to reverse the effect of
* exponent adjustment by 0xE0 less the necessary exponent adjustment by 0x70 due to difference in exponent bias.
* The floating-point multiplication hardware would ensure than Inf and NaN would retain their value on at least
* partially IEEE754-compliant implementations.
*
* Note that the above operations do not handle denormal inputs (where biased exponent == 0). However, they also do not
* operate on denormal inputs, and do not produce denormal results.
*/
const uint32_t exp_offset = UINT32_C(0xE0) << 23;
// const float exp_scale = 0x1.0p-112f;
uint32_t scale_bits = (uint32_t) 15 << 23;
float exp_scale_val;
std::memcpy(&exp_scale_val, &scale_bits, sizeof(exp_scale_val));
const float exp_scale = exp_scale_val;
const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
/*
* Convert denormalized half-precision inputs into single-precision results (always normalized).
* Zero inputs are also handled here.
*
* In a denormalized number the biased exponent is zero, and mantissa has on-zero bits.
* First, we shift mantissa into bits 0-9 of the 32-bit word.
*
* zeros | mantissa
* +---------------------------+------------+
* |0000 0000 0000 0000 0000 00|MM MMMM MMMM|
* +---------------------------+------------+
* Bits 10-31 0-9
*
* Now, remember that denormalized half-precision numbers are represented as:
* FP16 = mantissa * 2**(-24).
* The trick is to construct a normalized single-precision number with the same mantissa and thehalf-precision input
* and with an exponent which would scale the corresponding mantissa bits to 2**(-24).
* A normalized single-precision floating-point number is represented as:
* FP32 = (1 + mantissa * 2**(-23)) * 2**(exponent - 127)
* Therefore, when the biased exponent is 126, a unit change in the mantissa of the input denormalized half-precision
* number causes a change of the constructud single-precision number by 2**(-24), i.e. the same ammount.
*
* The last step is to adjust the bias of the constructed single-precision number. When the input half-precision number
* is zero, the constructed single-precision number has the value of
* FP32 = 1 * 2**(126 - 127) = 2**(-1) = 0.5
* Therefore, we need to subtract 0.5 from the constructed single-precision number to get the numerical equivalent of
* the input half-precision number.
*/
const uint32_t magic_mask = UINT32_C(126) << 23;
const float magic_bias = 0.5f;
const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
/*
* - Choose either results of conversion of input as a normalized number, or as a denormalized number, depending on the
* input exponent. The variable two_w contains input exponent in bits 27-31, therefore if its smaller than 2**27, the
* input is either a denormal number, or zero.
* - Combine the result of conversion of exponent and mantissa with the sign of the input number.
*/
const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
const uint32_t result = sign |
(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
return fp32_from_bits(result);
}
/*
* Convert a 32-bit floating-point number in IEEE single-precision format to a 16-bit floating-point number in
* IEEE half-precision format, in bit representation.
*
* @note The implementation relies on IEEE-like (no assumption about rounding mode and no operations on denormals)
* floating-point operations and bitcasts between integer and floating-point variables.
*/
inline uint16_t fp16_ieee_from_fp32_value(float f) {
// const float scale_to_inf = 0x1.0p+112f;
// const float scale_to_zero = 0x1.0p-110f;
uint32_t scale_to_inf_bits = (uint32_t) 239 << 23;
uint32_t scale_to_zero_bits = (uint32_t) 17 << 23;
float scale_to_inf_val, scale_to_zero_val;
std::memcpy(&scale_to_inf_val, &scale_to_inf_bits, sizeof(scale_to_inf_val));
std::memcpy(&scale_to_zero_val, &scale_to_zero_bits, sizeof(scale_to_zero_val));
const float scale_to_inf = scale_to_inf_val;
const float scale_to_zero = scale_to_zero_val;
float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
const uint32_t w = fp32_to_bits(f);
const uint32_t shl1_w = w + w;
const uint32_t sign = w & UINT32_C(0x80000000);
uint32_t bias = shl1_w & UINT32_C(0xFF000000);
if (bias < UINT32_C(0x71000000)) {
bias = UINT32_C(0x71000000);
}
base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
const uint32_t bits = fp32_to_bits(base);
const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
const uint32_t nonsign = exp_bits + mantissa_bits;
return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
}
} // namespace detail
struct alignas(2) Half {
unsigned short x;
struct from_bits_t {};
static constexpr from_bits_t from_bits() {
return from_bits_t();
}
// HIP wants __host__ __device__ tag, CUDA does not
#ifdef __HIP_PLATFORM_HCC__
C10_HOST_DEVICE Half() = default;
#else
Half() = default;
#endif
constexpr C10_HOST_DEVICE Half(unsigned short bits, from_bits_t) : x(bits){};
inline C10_HOST_DEVICE Half(float value);
inline C10_HOST_DEVICE operator float() const;
#if defined(__CUDACC__) || defined(__HIPCC__)
inline C10_HOST_DEVICE Half(const __half& value);
inline C10_HOST_DEVICE operator __half() const;
#endif
};
// This is just a placeholder for whatever complex representation we
// end up deciding to use for half-precision complex numbers.
struct alignas(4) ComplexHalf {
Half real_;
Half imag_;
ComplexHalf() = default;
Half real() const {
return real_;
}
Half imag() const {
return imag_;
}
inline ComplexHalf(std::complex<float> value)
: real_(value.real()), imag_(value.imag()) {}
inline operator std::complex<float>() const {
return {real_, imag_};
}
};
template <typename T>
struct is_complex_t : public std::false_type {};
template <typename T>
struct is_complex_t<std::complex<T>> : public std::true_type {};
template <>
struct is_complex_t<ComplexHalf> : public std::true_type {};
// Extract double from std::complex<double>; is identity otherwise
// TODO: Write in more idiomatic C++17
template <typename T>
struct scalar_value_type {
using type = T;
};
template <typename T>
struct scalar_value_type<std::complex<T>> {
using type = T;
};
template <>
struct scalar_value_type<ComplexHalf> {
using type = Half;
};
// The old implementation of Converter as a function made nvcc's head explode
// when we added std::complex on top of the specializations for CUDA-only types
// like __half, so I rewrote it as a templated class (so, no more overloads,
// just (partial) specialization).
template <typename To, typename From, typename Enable = void>
struct Converter {
To operator()(From f) {
return static_cast<To>(f);
}
};
template <typename To, typename From>
To convert(From from) {
return Converter<To, From>()(from);
}
template <typename To, typename FromV>
struct Converter<
To,
std::complex<FromV>,
typename std::enable_if<
c10::guts::negation<is_complex_t<To>>::value>::type> {
To operator()(std::complex<FromV> f) {
return static_cast<To>(f.real());
}
};
// In some versions of MSVC, there will be a compiler error when building.
// C4146: unary minus operator applied to unsigned type, result still unsigned
// It can be addressed by disabling the following warning.
#ifdef _MSC_VER
#pragma warning( push )
#pragma warning( disable : 4146 )
#endif
// skip isnan and isinf check for integral types
template <typename To, typename From>
typename std::enable_if<std::is_integral<From>::value, bool>::type overflows(
From f) {
using limit = std::numeric_limits<typename scalar_value_type<To>::type>;
if (!limit::is_signed && std::numeric_limits<From>::is_signed) {
// allow for negative numbers to wrap using two's complement arithmetic.
// For example, with uint8, this allows for `a - b` to be treated as
// `a + 255 * b`.
return f > limit::max() ||
(f < 0 && -static_cast<uint64_t>(f) > limit::max());
} else {
return f < limit::lowest() || f > limit::max();
}
}
#ifdef _MSC_VER
#pragma warning( pop )
#endif
template <typename To, typename From>
typename std::enable_if<std::is_floating_point<From>::value, bool>::type
overflows(From f) {
using limit = std::numeric_limits<typename scalar_value_type<To>::type>;
if (limit::has_infinity && std::isinf(static_cast<double>(f))) {
return false;
}
if (!limit::has_quiet_NaN && (f != f)) {
return true;
}
return f < limit::lowest() || f > limit::max();
}
template <typename To, typename From>
typename std::enable_if<is_complex_t<From>::value, bool>::type overflows(
From f) {
// casts from complex to real are considered to overflow if the
// imaginary component is non-zero
if (!is_complex_t<To>::value && f.imag() != 0) {
return true;
}
// Check for overflow componentwise
// (Technically, the imag overflow check is guaranteed to be false
// when !is_complex_t<To>, but any optimizer worth its salt will be
// able to figure it out.)
return overflows<
typename scalar_value_type<To>::type,
typename From::value_type>(f.real()) ||
overflows<
typename scalar_value_type<To>::type,
typename From::value_type>(f.imag());
}
template <typename To, typename From>
To checked_convert(From f, const char* name) {
if (overflows<To, From>(f)) {
std::ostringstream oss;
oss << "value cannot be converted to type " << name
<< " without overflow: " << f;
throw std::domain_error(oss.str());
}
return convert<To, From>(f);
}
C10_API std::ostream& operator<<(std::ostream& out, const Half& value);
} // namespace c10
#include <c10/util/Half-inl.h>
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