Match FastVideo's existing depth: VideoGenerator is the top-level
inference object with no Runner above it; loops live in scripts.
Eval should mirror that — Evaluator is the top-level scoring object,
EvalWorker × N is the layer below, and end-to-end pipelines (prompts
→ generate → score) are scripts, not classes.
Removed:
- fastvideo/eval/runner.py (EvalRunner + classmethod constructors).
- EvalRunner export from fastvideo.eval.
Added:
- fastvideo/eval/io/paths.py with sanitize_prompt, default_filename,
glob_videos, build_eval_kwargs as free functions. The reusable bits
of the runner survive; the class wrapping them does not.
Rewritten:
- scripts/eval/run_vbench_e2e.py is now top-to-bottom procedural:
parse_args → dataset → optional generate() loop → optional score()
loop. Reads in one pass; no classmethod indirection to chase.
Parity verified on fs-mbz-gpu-085 against runs/vbench_smoke/videos/
(2 videos × 3 metrics, dimensions=subject_consistency):
- 1-GPU run (results_v4.json) is byte-identical to v3 baseline.
- 2-GPU run (results_v4_2gpu.json) is byte-identical to v3 baseline
(order-preserving fan-out via Evaluator.evaluate(samples=[...])).
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