Research Radar · Experimental implementation
ANE Trainer
A small-model training workflow with Apple Silicon detection and a placeholder ANE abstraction.
What it investigates
ANE Trainer investigates how a conventional small-model training workflow could expose an Apple Neural Engine boundary while retaining a CPU execution path.
Implementation record
The reference package exposes dataset loading and caching, model construction, a CPU training step, an ANE-aware forward-pass abstraction, and an Apple Silicon check. The current ANE branch is stubbed and the walkthrough executes on CPU.
Public record
The linked research item is the public source recorded for this Research Radar build. It provides context for the implementation; this page does not claim to reproduce its results. The repository and its documentation are the current public materials for inspecting the build itself.
Scope and limitations
The public implementation does not currently train or run inference on ANE hardware. It provides an interface intended for future ANE integration and makes no training-speed or accelerator-support claim.