ml_dtypes¶
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 float8_*: several experimental 8-bit floating point representations including: float8_e4m3b11fnuz float8_e4m3fn float8_e4m3fnuz float8_e5m2 float8_e5m2fnuz
homepage: https://github.com/jax-ml/ml_dtypes
Available installations¶
| ml_dtypes version | Supported CPU targets | Supported GPU targets | EESSI version | Module |
|---|---|---|---|---|
| 0.3.2 | generic: aarch64, x86_64Arm: a64fx, neoverse_n1, neoverse_v1, nvidia/graceAMD: zen2, zen3, zen4Intel: haswell, skylake_avx512, sapphirerapids, icelake, cascadelake |
(none) | 2023.06 | ml_dtypes/0.3.2-gfbf-2023a |
Extensions¶
Overview of extensions included in ml_dtypes installations
etils¶
etils version |
ml_dtypes modules that include it |
|---|---|
| 1.6.0 | ml_dtypes/0.3.2-gfbf-2023a |
ml_dtypes¶
ml_dtypes version |
ml_dtypes modules that include it |
|---|---|
| 0.3.2 | ml_dtypes/0.3.2-gfbf-2023a |
opt_einsum¶
opt_einsum version |
ml_dtypes modules that include it |
|---|---|
| 3.3.0 | ml_dtypes/0.3.2-gfbf-2023a |