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Fix ordering of complex64 with NaNs #4519

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Fix ordering of complex64 with NaNs #4519

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4 changes: 2 additions & 2 deletions mlx/backend/cpu/simd/base_simd.h
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Original file line number Diff line number Diff line change
Expand Up @@ -244,7 +244,7 @@ Simd<T, 1> maximum(Simd<T, 1> a_, Simd<T, 1> b_) {
T a = a_.value;
T b = b_.value;
if constexpr (!std::is_integral_v<T>) {
if (std::isnan(a)) {
if (mlx::core::isnan(a)) {
return a;
}
}
Expand All @@ -256,7 +256,7 @@ Simd<T, 1> minimum(Simd<T, 1> a_, Simd<T, 1> b_) {
T a = a_.value;
T b = b_.value;
if constexpr (!std::is_integral_v<T>) {
if (std::isnan(a)) {
if (mlx::core::isnan(a)) {
return a;
}
}
Expand Down
17 changes: 8 additions & 9 deletions mlx/backend/cpu/sort.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,6 @@

#include <algorithm>
#include <cassert>
#include <cmath>
#include <numeric>

#include "mlx/backend/common/utils.h"
Expand All @@ -19,9 +18,9 @@ namespace {
template <typename T>
bool nan_aware_less(T a, T b) {
if constexpr (is_floating_point_v<T> || std::is_same_v<T, complex64_t>) {
if (std::isnan(a))
if (mlx::core::isnan(a))
return false;
if (std::isnan(b))
if (mlx::core::isnan(b))
return true;
}
return a < b;
Expand Down Expand Up @@ -206,10 +205,10 @@ void argsort(const array& in, array& out, int axis) {
auto v2 = data_ptr[b * in_stride];

// Handle NaNs (place them at the end)
if constexpr (is_floating_point_v<T>) {
if (std::isnan(v1))
if constexpr (is_floating_point_v<T> || std::is_same_v<T, complex64_t>) {
if (mlx::core::isnan(v1))
return false;
if (std::isnan(v2))
if (mlx::core::isnan(v2))
return true;
}

Expand Down Expand Up @@ -315,10 +314,10 @@ void argpartition(const array& in, array& out, int axis, int kth) {
auto v2 = data_ptr[b * in_stride];

// Handle NaNs (place them at the end)
if constexpr (is_floating_point_v<T>) {
if (std::isnan(v1))
if constexpr (is_floating_point_v<T> || std::is_same_v<T, complex64_t>) {
if (mlx::core::isnan(v1))
return false;
if (std::isnan(v2))
if (mlx::core::isnan(v2))
return true;
}

Expand Down
22 changes: 22 additions & 0 deletions python/tests/test_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -593,6 +593,11 @@ def test_minimum(self):
self.assertTrue(math.isnan(mx.minimum(a, b).item()))
self.assertTrue(math.isnan(mx.minimum(b, a).item()))

# A NaN in either part of the first argument propagates.
a = mx.array([complex(3, float("nan"))])
b = mx.array([2 + 0j])
self.assertTrue(mx.array_equal(mx.minimum(a, b), a, equal_nan=True))

def test_maximum(self):
x = mx.array([0.0, -5, 10.0])
y = mx.array([1.0, -7.0, 3.0])
Expand All @@ -605,6 +610,11 @@ def test_maximum(self):
self.assertTrue(math.isnan(mx.maximum(a, b).item()))
self.assertTrue(math.isnan(mx.maximum(b, a).item()))

# A NaN in either part of the first argument propagates.
a = mx.array([complex(1, float("nan"))])
b = mx.array([2 + 0j])
self.assertTrue(mx.array_equal(mx.maximum(a, b), a, equal_nan=True))

def test_floor(self):
x = mx.array([-22.03, 19.98, -27, 9, 0.0, -np.inf, np.inf])
expected = [-23, 19, -27, 9, 0, -np.inf, np.inf]
Expand Down Expand Up @@ -4274,6 +4284,11 @@ def test_sort_nan(self):
expected = mx.array([0.0 + 1j, 2.0 + 1j, 3.0 + 1j, mx.nan + 2j])
self.assertTrue(mx.array_equal(mx.sort(x), expected, equal_nan=True))

# A NaN in the imaginary part also sorts last.
x = mx.array([3.0 + 1j, complex(1.0, mx.nan), 2.0 + 1j, 0.0 + 1j])
expected = mx.array([0.0 + 1j, 2.0 + 1j, 3.0 + 1j, complex(1.0, mx.nan)])
self.assertTrue(mx.array_equal(mx.sort(x), expected, equal_nan=True))

def test_argsort_nan(self):
for dtype in [mx.float32, mx.float16, mx.bfloat16]:
with self.subTest(dtype=dtype):
Expand All @@ -4283,6 +4298,13 @@ def test_argsort_nan(self):
sorted_x = mx.take(x, indices)
self.assertTrue(mx.array_equal(sorted_x, expected, equal_nan=True))

# Also test complex values
for nan_val in [mx.nan + 2j, complex(1.0, mx.nan)]:
x = mx.array([3.0 + 1j, nan_val, 2.0 + 1j, 0.0 + 1j])
expected = mx.array([0.0 + 1j, 2.0 + 1j, 3.0 + 1j, nan_val])
sorted_x = mx.take(x, mx.argsort(x))
self.assertTrue(mx.array_equal(sorted_x, expected, equal_nan=True))

def test_to_from_fp8(self):
vals = mx.array(
[448, 256, 192, 128, 96, 64, 48, 32, 24, 16, 12, 8, 6, 4, 3, 2, 0.015625]
Expand Down