python-ml-dtypes

stand-alone implementation of several NumPy dtype extensions

`ml_dtypes` is a stand-alone implementation of several NumPy dtype extensions used in machine learning libraries, including: - [`bfloat16`](<a href="https://en.wikipedia.org/wiki/Bfloat16_floating-point_format):">https://en.wikipedia.org/wiki/Bfloat16_floating-point_format):</a> an alternative to the standard [`float16`](<a href="https://en.wikipedia.org/wiki/Half-precision_floating-point_format">https://en.wikipedia.org/wiki/Half-precision_floating-point_format</a> ) format - `float8_*`: several experimental 8-bit floating point representations including: * `float8_e3m4` * `float8_e4m3` * `float8_e4m3b11fnuz` * `float8_e4m3fn` * `float8_e4m3fnuz` * `float8_e5m2` * `float8_e5m2fnuz` - Microscaling (MX) sub-byte floating point representations including: * `float4_e2m1fn` * `float6_e2m3fn` * `float6_e3m2fn` - `int2`, `int4`, `uint2` and `uint4`: low precision integer types.