Principle:Facebookresearch Audiocraft Sample Management
| Knowledge Sources | |
|---|---|
| Domains | Training, Evaluation |
| Last Updated | 2026-02-14 01:00 GMT |
Overview
A sample storage and retrieval strategy that organizes generated audio outputs by epoch for qualitative comparison during model training.
Description
Sample Management provides a structured approach to storing audio generation outputs during training. Each solver's generate stage produces audio samples that are saved alongside their ground truth references, organized by epoch. This enables both automated metric evaluation and qualitative listening comparisons across training progress.
Usage
Use this principle in any audio generation training pipeline where tracking generated output quality across epochs is needed.
Theoretical Basis
Pseudo-code:
# Abstract sample management (NOT actual implementation)
for each epoch:
generated_audio = model.generate(conditions)
save(generated_audio, ground_truth, epoch=epoch)
metrics = evaluate(generated_audio, ground_truth)
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