Support for machine learning dtypes

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
machine-learning, numpy, python, pytorch
Domain
machine-learning

Research direction

The issue names no files, tests, or entry points. Begin by reviewing dtype support across JAX, PyTorch, NumPy, and ml_dtypes, then define which bfloat16, float8*, float4, uint4/int4, and uint2/int2 types are required; done means an agreed support plan and scope.

Written by the indexing model from the issue text.

Description

question

I am building a reference runtime for ONNX using this library, which needs to support data types commonly used in machine learning, e.g. bfloat16, float8*, float4, and lower bit ints like (u)int4 and (u)int2. These types exist in frameworks like jax, pytorch and numpy (via the ml_dtypes package). Is there a plan to support these datatypes?

Dominant language
Python
Stars
131
Forks
49
Avg merge
2d 8h
Merged PRs (30d)
6

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