Description
Provides NumPy dtype extensions commonly used in machine-learning frameworks, such as lower-precision numeric formats. It helps Python ML libraries share and process model data with consistent type behavior.
This is infrastructure for numerical computing. Lower-precision data types can change accuracy, so model results should be validated for the target workload.