Source: ml-dtypes
Section: python
Homepage: https://github.com/jax-ml/ml_dtypes
Priority: optional
Standards-Version: 4.7.0
Vcs-Git: https://salsa.debian.org/deeplearning-team/ml-dtypes.git
Vcs-Browser: https://salsa.debian.org/deeplearning-team/ml-dtypes
Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Uploaders: Mo Zhou <lumin@debian.org>
Build-Depends: debhelper-compat (= 13),
               dh-sequence-python3,
               python3-setuptools,
               python3-all,
               python3-all-dev,
               python3-numpy,
               python3-numpy-dev,
               python3-pytest <!nocheck>,
               python3-absl <!nocheck>,

Package: ml-dtypes-dev
Architecture: any
Depends: ${misc:Depends},
         ${python3:Depends},
         ${shlibs:Depends},
Description: Several NumPy dtype extensions used in machine learning (development files)
 ml_dtypes is a stand-alone implementation of several NumPy dtype extensions
 used in machine learning libraries, including:
 .
  * bfloat16: an alternative to the standard float16 format
  * 8-bit floating point representations, parameterized by number of exponent
    and mantissa bits, as well as the bias (if any) and representability of
    infinity, NaN, and signed zero.
     float8_e3m4
     float8_e4m3
     float8_e4m3b11fnuz
     float8_e4m3fn
     float8_e4m3fnuz
     float8_e5m2
     float8_e5m2fnuz
     float8_e8m0fnu
  * Microscaling (MX) sub-byte floating point representations:
     float4_e2m1fn
     float6_e2m3fn
     float6_e3m2fn
  * Narrow integer encodings:
     int2
     int4
     uint2
     uint4
 .
 This package contains header files and other data necessary for developing with
 ml_dtypes.

Package: python3-ml-dtypes
Architecture: any
Depends: ${misc:Depends},
	 ${python3:Depends},
         ${shlibs:Depends},
Description: Several NumPy dtype extensions used in machine learning
 ml_dtypes is a stand-alone implementation of several NumPy dtype extensions
 used in machine learning libraries, including:
 .
  * bfloat16: an alternative to the standard float16 format
  * 8-bit floating point representations, parameterized by number of exponent
    and mantissa bits, as well as the bias (if any) and representability of
    infinity, NaN, and signed zero.
     float8_e3m4
     float8_e4m3
     float8_e4m3b11fnuz
     float8_e4m3fn
     float8_e4m3fnuz
     float8_e5m2
     float8_e5m2fnuz
     float8_e8m0fnu
  * Microscaling (MX) sub-byte floating point representations:
     float4_e2m1fn
     float6_e2m3fn
     float6_e3m2fn
  * Narrow integer encodings:
     int2
     int4
     uint2
     uint4