xnn.common.benchmark.runner#
Score pre-trained models on one dataset and tabulate their errors.
Benchmarking does one thing: for every model in the config it builds the
architecture, loads the entry’s checkpoint into it, scores it on the
benchmark dataset with the configured metrics, and writes a comparison table.
It does not train or evaluate during training – produce the checkpoints with
xnn train (or any other route) first.
Model building reuses the model registry and
ForceStressOutput, so a benchmarked model is built
and run exactly as it would be in a single run. The benchmark dataset is built
once per cutoff, so models sharing a cutoff share one neighbor-list build.
Functions
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Convenience wrapper: build a |
Classes
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Run a |