ceos/unsloth
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Trim the comments across the diffusion backend

Browse source 
Comment-only pass over the Python this PR touches: drop what the code already
says, collapse multi-line explanations that still read on one line, and keep
the reasoning that is not recoverable from the code. No code, docstring
semantics or behaviour changes; verified with an AST comparison against the
previous revision, and the backend suite is unchanged (same 37 environment
failures as before: the API integration tests that need a live keyed server,
the flash-attn install hooks, and the GPU memory fields).
This commit is contained in:
Daniel Han 2026-07-26 20:30:46 +00:00
commit 36df317293
113 changed files with 3389 additions and 4087 deletions
Download patch file Download diff file Expand all files Collapse all files

14
scripts/diffusion_quality.py
View file

@ -67,9 +67,8 @@ def _to_rgb(path_or_img: Any) -> Any:
return np.asarray(img.convert("RGB"), dtype = np.float64)
# Finite PSNR (dB) a perfect (inf) sample is capped to when averaged with imperfect ones, so a
# lossless render counts as excellent without hiding diverged samples. Well above the ~37 dB
# compile and ~21 dB quant noise floors this harness reports.
# Finite PSNR (dB) cap for perfect (inf) samples, so a lossless render averages as excellent
# without hiding diverged ones. Well above the ~37 dB compile and ~21 dB quant noise floors.
_PERFECT_MATCH_PSNR = 100.0
@ -192,8 +191,7 @@ def _wait_for_load(backend: Any, timeout_s: int = 3600) -> None:
def _hf_file_size_mib(repo: str, filename: str) -> Optional[int]:
# A local model dir / file: stat it directly. The Hub lookup below returns None for
# a local path, which would drop every candidate from _recommend (file_size_mib None).
# Local paths: stat directly, since the Hub lookup returns None and _recommend would drop them.
try:
local = Path(repo).expanduser()
if local.is_dir():
@ -286,10 +284,8 @@ def _compare(
clip_sim.append(clip.image_similarity(img, ref))
def _mean(xs: list[float]) -> Optional[float]:
# +inf marks an identical render (reference vs itself, or a lossless quant/offload)
# scoring PSNR=inf -- the case this harness verifies. Report inf ONLY when every sample is
# inf; a mix means some renders diverged, so a bare inf would mask them. Cap the perfect
# ones to a high finite PSNR and average so the drift still shows. (Only PSNR is ever inf.)
# +inf marks an identical render. Report inf only when every sample is inf; otherwise cap the
# perfect ones to a high finite PSNR so partial drift still shows. (Only PSNR is ever inf.)
if not xs:
return None
if all(x == math.inf for x in xs):