Pipelines path → tensor decode behind GPU metric compute via a new
VideoPool, so multi-sample eval runs no longer serialize disk I/O and
metric work. The Evaluator owns one pool per evaluate(samples=...)
call; each EvalWorker is a single-GPU consumer that grabs decoded
samples from the shared queue (work-stealing across replicas when
num_gpus > 1).
Worker pre-uploads video/reference to its device once per sample so
every metric in the loop consumes the same GPU-resident tensor (no
per-metric .to(device) traffic).
SSIM and PSNR move to the GPU — at 1080p × 121 frames the CPU path
was both slow (5–10 s/pair) and contended with the loader thread for
DDR bandwidth. LPIPS gains a chunk_size knob (default 8) that caps
peak from ~60 GB to ~5 GB with bit-identical output. Optical-flow
metrics drop chunk_size to 1 because DPFlow's cost volume is ~4 GB
per frame pair at 1080p (matches mhuo/ptlflow upstream).
physics_iq and a handful of vbench metrics drop their list-batch
shims — the per-sample contract is now uniform across the suite.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
