Principle:Ggml org Llama cpp Eval Callbacks
| Knowledge Sources | |
|---|---|
| Domains | Debugging, Callbacks |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
Eval Callbacks is the principle of hooking into the model evaluation pipeline to observe or modify intermediate computation results.
Description
This principle covers the callback mechanism that allows external code to be invoked at specific points during model evaluation (forward pass). Callbacks can inspect intermediate tensor values, collect statistics, log computation progress, or even modify tensor data in-flight. This mechanism provides extensibility without modifying the core inference code.
Usage
Apply this principle when you need to monitor the inference process in real-time, collect activation statistics for analysis, implement custom logging of intermediate values, or debug model behavior by inspecting layer-by-layer outputs.
Theoretical Basis
The eval callback system follows the observer pattern, where the inference engine invokes registered callback functions at predefined points in the computation graph evaluation. Each callback receives information about the current tensor being computed, including its name, shape, data type, and optionally its data. This design decouples observation logic from computation logic, allowing any number of monitoring or debugging tools to be attached without modifying the inference code. The callback interface is designed to be lightweight so that the overhead of checking for registered callbacks is minimal when no callbacks are active.