mlx/mlx/backend/metal/kernels/reduction/ops.h
jhavukainen 8b9a3f3cea
Align mlx::core::max op nan propagation with NumPy (#2339)
* Make max op NaN propagation rules align with numpy

* Adding benchmarks and testing for max op nanpropagation

* Pre-commit formatting

* Fix max complex64 nan propagation and add test

* Improve the cpp unittest

* Only check nans on non-integral types in simd_reduce_impl.

* Cleanup using namespace alias

* Add cpu Max nanpropagation. Fix a small fib in cpu max dispatch data types for int8/int16.

* Make the max nanpropagation test more meaningful for integer types

* Remove tuple unpacking syntax to comply with earlier python versions. Add cuda skip to nanpropagation tests, fix cuda implementation in a separate PR.
2025-07-09 11:26:27 -07:00

241 lines
5.7 KiB
C++

// Copyright © 2023-2024 Apple Inc.
#pragma once
#include <metal_atomic>
#include <metal_simdgroup>
#define DEFINE_SIMD_REDUCE() \
template <typename T, metal::enable_if_t<sizeof(T) < 8, bool> = true> \
T simd_reduce(T val) { \
return simd_reduce_impl(val); \
} \
\
template <typename T, metal::enable_if_t<sizeof(T) == 8, bool> = true> \
T simd_reduce(T val) { \
for (short i = simd_size / 2; i > 0; i /= 2) { \
val = operator()(val, simd_shuffle_down(val, i)); \
} \
return val; \
}
static constant constexpr const uint8_t simd_size = 32;
union bool4_or_uint {
bool4 b;
unsigned int i;
};
struct None {
template <typename T>
void atomic_update(device mlx_atomic<T>* out, T val, size_t offset = 0) {
mlx_atomic_store_explicit(out, val, offset);
}
};
template <typename U = bool>
struct And {
DEFINE_SIMD_REDUCE()
bool simd_reduce_impl(bool val) {
return simd_all(val);
}
static constexpr constant bool init = true;
void atomic_update(
device mlx_atomic<unsigned int>* out,
bool val,
int elem_idx,
size_t offset = 0) {
if (!val) {
bool4_or_uint update;
update.b = {true, true, true, true};
update.b[elem_idx] = false;
mlx_atomic_fetch_and_explicit(out, update.i, offset);
}
}
void
atomic_update(device mlx_atomic<bool>* out, bool val, size_t offset = 0) {
if (!val) {
mlx_atomic_store_explicit(out, val, offset);
}
}
// Non atomic update
void update(device bool* out, bool val) {
*out &= val;
}
// Operator
bool operator()(bool a, bool b) {
return a && b;
}
};
template <typename U = bool>
struct Or {
DEFINE_SIMD_REDUCE()
bool simd_reduce_impl(bool val) {
return simd_any(val);
}
static constexpr constant bool init = false;
void atomic_update(
device mlx_atomic<unsigned int>* out,
bool val,
int elem_idx,
size_t offset = 0) {
if (val) {
bool4_or_uint update;
update.b = {false, false, false, false};
update.b[elem_idx] = true;
mlx_atomic_fetch_or_explicit(out, update.i, offset);
}
}
void
atomic_update(device mlx_atomic<bool>* out, bool val, size_t offset = 0) {
if (val) {
mlx_atomic_store_explicit(out, val, offset);
}
}
// Non atomic update
void update(device bool* out, bool val) {
*out |= val;
}
// Operator
bool operator()(bool a, bool b) {
return a || b;
}
};
template <typename U>
struct Sum {
DEFINE_SIMD_REDUCE()
template <typename T>
T simd_reduce_impl(T val) {
return simd_sum(val);
}
static constexpr constant U init = U(0);
template <typename T>
void atomic_update(device mlx_atomic<T>* out, T val, size_t offset = 0) {
mlx_atomic_fetch_add_explicit(out, val, offset);
}
// Operator
U operator()(U a, U b) {
return a + b;
}
};
template <typename U>
struct Prod {
DEFINE_SIMD_REDUCE()
template <typename T>
T simd_reduce_impl(T val) {
return simd_product(val);
}
static constexpr constant U init = U(1);
template <typename T>
void atomic_update(device mlx_atomic<T>* out, T val, size_t offset = 0) {
mlx_atomic_fetch_mul_explicit(out, val, offset);
}
// Operator
U operator()(U a, U b) {
return a * b;
}
};
template <typename U>
struct Min {
DEFINE_SIMD_REDUCE()
template <typename T>
T simd_reduce_impl(T val) {
return simd_min(val);
}
static constexpr constant U init = Limits<U>::max;
template <typename T>
void atomic_update(device mlx_atomic<T>* out, T val, size_t offset = 0) {
mlx_atomic_fetch_min_explicit(out, val, offset);
}
// Operator
U operator()(U a, U b) {
return a < b ? a : b;
}
};
template <typename U>
struct Max {
DEFINE_SIMD_REDUCE()
template <typename T>
metal::enable_if_t<metal::is_integral_v<T>, T> simd_reduce_impl(T val) {
return simd_max(val);
}
template <typename T>
metal::enable_if_t<!metal::is_integral_v<T>, T> simd_reduce_impl(T val) {
if (simd_any(val != val)) {
return static_cast<T>(NAN);
}
return simd_max(val);
}
static constexpr constant U init = Limits<U>::min;
template <typename T>
void atomic_update(device mlx_atomic<T>* out, T val, size_t offset = 0) {
mlx_atomic_fetch_max_explicit(out, val, offset);
}
// Operator
template <typename T>
metal::enable_if_t<metal::is_integral_v<T>, T> operator()(T a, T b) {
return a > b ? a : b;
}
template <typename T>
metal::enable_if_t<!metal::is_integral_v<T>, T> operator()(T a, T b) {
if (metal::isnan(a) || metal::isnan(b)) {
return static_cast<T>(NAN);
} else {
return a > b ? a : b;
}
}
template <>
complex64_t operator()(complex64_t a, complex64_t b) {
bool real_is_nan = metal::isnan(a.real) || metal::isnan(b.real);
bool imag_is_nan = metal::isnan(a.imag) || metal::isnan(b.imag);
if (!real_is_nan && !imag_is_nan) {
return a > b ? a : b;
} else if (real_is_nan && !imag_is_nan) {
return complex64_t(
static_cast<float>(NAN), a.imag > b.imag ? a.imag : b.imag);
} else if (!real_is_nan && imag_is_nan) {
return complex64_t(
a.real > b.real ? a.real : b.real, static_cast<float>(NAN));
} else {
return complex64_t(static_cast<float>(NAN), static_cast<float>(NAN));
}
}
};