struct (un)packing of half-precision `nan` floats is non-invertible

[seh-dev]

Bug report

Bug description:

I noticed that chaining struct.unpack() and struct.pack() for IEEE 754 Half Precision floats (e) is non-invertible for nan. E.g.:

import struct

original_bytes = b'\xff\xff'

unpacked_float = struct.unpack('e', original_bytes)[0] # nan
repacked_bytes = struct.pack('e', unpacked_float) # b'\x00\xfe' != b'\xff\xff'

IEEE nans aren't unique, so this isn't that surprising... However I found it curious that the same behavior is not exhibited for float (f) or double (d) format, where every original bit pattern I tested could be recovered from the unpacked nan object.

Is this by design?

Here's a quick pytest script that tests over a broad range of nan/inf/-inf cases for each encoding format.

# /// script
# requires-python = ">=3.11"
# dependencies = ["pytest"]
# ///
import struct
import pytest


# Floating Point Encodings Based on IEEE 754 per https://en.wikipedia.org/wiki/IEEE_754#Basic_and_interchange_formats
# binary 16 (half precision) - 1 bit sign, 5 bit exponent, 11 bit significand
# binary 32 (single precision) - 1 bit sign, 8 bit exponent, 23 bit significand
# binary 64 (double precision) - 1 bit sign, 11 bit exponent, 52 bit significand


MAX_TEST_CASES = 100000 # limit number of bit patterns being sampled so we aren't waiting too long


@pytest.mark.parametrize(["precision_format", "precision", "exponent_bits"], [("f", 32, 8), ("d", 64, 11), ("e", 16, 5)])
@pytest.mark.parametrize("sign_bit", [0, 1])
@pytest.mark.parametrize("endianness", ["little", "big"])
def test_struct_floats(precision_format: str, precision: int, exponent_bits: int, sign_bit: int, endianness: str):
 significand_bits = precision - exponent_bits - 1

 n_tests = min(MAX_TEST_CASES, 2**significand_bits)

 significand_patterns = [significand_bits * "0", significand_bits * "1"] + [
 bin(i + 1)[2:] for i in range(1, 2**significand_bits, 2**significand_bits // n_tests)
 ]

 for i in range(n_tests):
 binary = str(sign_bit) + "1" * exponent_bits + significand_patterns[i]
 if endianness == "big":
 format = ">" + precision_format
 elif endianness == "little":
 format = "<" + precision_format
 else:
 raise NotImplementedError()

 test_bytes = int(binary, base=2).to_bytes(precision // 8, endianness)

 unpacked = struct.unpack(format, test_bytes)
 assert len(unpacked) == 1

 repacked = struct.pack(format, unpacked[0])

 assert (
 repacked == test_bytes
 ), f"struct pack/unpack was not invertible for format {format} with raw value: {test_bytes} -> unpacks to {unpacked[0]}, repacks to {repacked}"

if __name__ == "__main__":
 pytest.main([__file__])

CPython versions tested on:

3.13, 3.11, 3.12

Operating systems tested on:

Linux, Windows

Linked PRs

• gh-130317: fix PyFloat_Pack/Unpack[24] for NaN's with payload #130452
• gh-130317: Fix strict aliasing in PyFloat_Pack8() #133150
• gh-130317: Skip test_pack_unpack_roundtrip_for_nans() on x86 #133155
• gh-130317: fix test_pack_unpack_roundtrip() and add docs #133204
• gh-130317: Fix SNaN broken tests on HP PA RISC #140452
• [3.14] gh-130317: Fix SNaN broken tests on HP PA RISC (GH-140452) #140467

[skirpichev]

It seems you are on IEEE-platform, or unpacking special values will fail for float and double formats. So for those formats, pack/unpack functions work by copying bits.

But not PyFloat_Pack2() and PyFloat_Unpack2(). E.g. the later just ignores all payload in the nan value and maps data to one or another quiet nan:

cpython/Objects/floatobject.c

Lines 2402 to 2405 in 12e1d30

	else {
	/* NaN */
	return sign ? -fabs(Py_NAN) : fabs(Py_NAN);
	}

The PyFloat_Pack2() also ignores all payload from double nan:

cpython/Objects/floatobject.c

Lines 2050 to 2059 in 12e1d30

	else if (isnan(x)) {
	/* There are 2046 distinct half-precision NaNs (1022 signaling and
	1024 quiet), but there are only two quiet NaNs that don't arise by
	quieting a signaling NaN; we get those by setting the topmost bit
	of the fraction field and clearing all other fraction bits. We
	choose the one with the appropriate sign. */
	sign = (copysign(1.0, x) == -1.0);
	e = 0x1f;
	bits = 512;
	}

Is this by design?

Looks as a bug for me.

CC @mdickinson

Edit: assuming doubles are binary64, following patch fix your tests:

diff --git a/Objects/floatobject.c b/Objects/floatobject.c
index 3b72a1e7c3..e473fb72fe 100644
--- a/Objects/floatobject.c
+++ b/Objects/floatobject.c
@@ -2048,14 +2048,16 @@ PyFloat_Pack2(double x, char *data, int le)
 bits = 0;
 }
 else if (isnan(x)) {
- /* There are 2046 distinct half-precision NaNs (1022 signaling and
- 1024 quiet), but there are only two quiet NaNs that don't arise by
- quieting a signaling NaN; we get those by setting the topmost bit
- of the fraction field and clearing all other fraction bits. We
- choose the one with the appropriate sign. */
 sign = (copysign(1.0, x) == -1.0);
 e = 0x1f;
- bits = 512;
+
+ uint64_t v;
+
+ memcpy(&v, &x, sizeof(v));
+ bits = v & 0x1ff;
+ if (v & 0x800000000000) {
+ bits += 0x200;
+ }
 }
 else {
 sign = (x < 0.0);
@@ -2401,7 +2403,16 @@ PyFloat_Unpack2(const char *data, int le)
 }
 else {
 /* NaN */
- return sign ? -fabs(Py_NAN) : fabs(Py_NAN);
+ uint64_t v = ((sign? 0xff00000000000000 : 0x7f00000000000000)
+ + 0xf0000000000000);
+
+ if (f & 0x200) {
+ v += 0x800000000000;
+ f -= 0x200;
+ }
+ v += f;
+ memcpy(&x, &v, sizeof(v));
+ return x;
 }
 }
 

FYI: #55943. Probably the reason why payload was ignored is that the patch was adapted from numpy sources.

[skirpichev]

@tim-one, does it looks as an issue for you?

[skirpichev]

PR is ready for review: #130452

[vstinner]

Fixed in the main branch (future Python 3.14) by change 6157135. The change is not backported to 3.13 branch since it's a minor issue.

[vstinner]

I reopen the issue, there are failures on x86 (32-bit): #130452 (comment)