shaoxiongduan
d07a7691fe
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=[...])).
13 lines
350 B
Python
13 lines
350 B
Python
from fastvideo.eval.io.paths import (build_eval_kwargs, default_filename,
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glob_videos, sanitize_prompt)
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from fastvideo.eval.io.video import extract_frames, load_video
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__all__ = [
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"load_video",
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"extract_frames",
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"sanitize_prompt",
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"default_filename",
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"glob_videos",
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"build_eval_kwargs",
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]
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