I trained several models and computed a simple metrics summary for each of them. Now, those models (and their corresponding metrics.json files) are versioned by dvc and git and there is a git tag associated with each model.
Having the models trained and stored, I would like to enrich the metrics summary and go back and recompute it for each model – and store it in git as with the simple summary. This means the last part of the pipeline, say compute_metrics.py, will be changed and I would like to run dvc repro again. Is there a simple way of recomputing the metrics for all models (that is for all tags)?