python-gfloat 0.3-1 source package in Ubuntu
Changelog
python-gfloat (0.3-1) unstable; urgency=medium * New upstream release -- Scott Kitterman <email address hidden> Thu, 13 Jun 2024 00:15:48 -0400
Upload details
- Uploaded by:
- Debian Python Team
- Uploaded to:
- Sid
- Original maintainer:
- Debian Python Team
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Oracular | release | universe | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
python-gfloat_0.3-1.dsc | 2.2 KiB | b628a877fa4134865987071c08597c7e0193c111a92be6c8d7d9c0323c67c265 |
python-gfloat_0.3.orig.tar.gz | 42.8 KiB | b0a717a2bb296db5df21e7cd12800f336d107d777f0bcd91805bed34449f5bde |
python-gfloat_0.3-1.debian.tar.xz | 2.5 KiB | 43c176fa0c26a83a5f02e6e7ad04aa948b0b147c025ea031855ed2482a0b3713 |
Available diffs
- diff from 0.2.1-1 to 0.3-1 (22.6 KiB)
No changes file available.
Binary packages built by this source
- python-gfloat-doc: documentation for the gfloat Python library
An implementation of generic floating point encode/decode logic, handling
various current and proposed floating point types:
.
- IEEE 754: Binary16, Binary32
- OCP Float8: E5M2, E4M3
- IEEE WG P3109: P{p} for p in 1..7
- OCP MX Formats: E2M1, M2M3, E3M2, E8M0, INT8, and the MX block formats.
.
The library favours readability and extensibility over speed - for fast
implementations of these datatypes see, for example, ml_dtypes, bitstring, MX
PyTorch Emulation Library.
.
This package provides documentation for python3-gfloat.
- python3-gfloat: Python module of generic floating point encode/decode logic
An implementation of generic floating point encode/decode logic, handling
various current and proposed floating point types:
.
- IEEE 754: Binary16, Binary32
- OCP Float8: E5M2, E4M3
- IEEE WG P3109: P{p} for p in 1..7
- OCP MX Formats: E2M1, M2M3, E3M2, E8M0, INT8, and the MX block formats.
.
The library favours readability and extensibility over speed - for fast
implementations of these datatypes see, for example, ml_dtypes, bitstring, MX
PyTorch Emulation Library.