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Merge remote-tracking branch 'origin/image-generation' into diffusion-phase4-native

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# Conflicts:
#	scripts/diffusion_bench.py
#	scripts/diffusion_quality.py
#	studio/backend/core/inference/diffusion.py
#	studio/backend/core/inference/diffusion_device.py
#	studio/backend/core/inference/diffusion_families.py
#	studio/backend/core/inference/diffusion_memory.py
#	studio/backend/core/inference/diffusion_precision.py
#	studio/backend/core/inference/diffusion_speed.py
#	studio/backend/models/inference.py
#	studio/backend/routes/inference.py
#	studio/backend/tests/test_diffusion_backend.py
#	studio/backend/tests/test_diffusion_device.py
#	studio/backend/tests/test_diffusion_memory.py
#	studio/backend/tests/test_diffusion_precision.py
#	studio/backend/tests/test_diffusion_speed.py
This commit is contained in:
Daniel Han 2026-07-01 11:19:15 +00:00
commit 48628252bd
270 changed files with 22498 additions and 2729 deletions
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19
scripts/diffusion_bench.py
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@ -142,8 +142,10 @@ def _psnr(ref_png: Path, cand_png: Path) -> float:
import numpy as np
from PIL import Image
a = np.asarray(Image.open(ref_png).convert("RGB"), dtype = np.float64)
b = np.asarray(Image.open(cand_png).convert("RGB"), dtype = np.float64)
with Image.open(ref_png) as im_a:
a = np.asarray(im_a.convert("RGB"), dtype = np.float64)
with Image.open(cand_png) as im_b:
b = np.asarray(im_b.convert("RGB"), dtype = np.float64)
if a.shape != b.shape:
# Different geometry means the comparison is meaningless; report worst case.
return 0.0
@ -360,9 +362,14 @@ def _compare(args: argparse.Namespace) -> int:
print(" refusing noisy comparison (pass --force-compare to override).", flush = True)
return 2
# PSNR vs the stored reference image.
# PSNR vs the stored reference image. The baseline stores an absolute reference_png,
# which breaks if the baseline directory was copied/moved, so fall back to reference.png
# next to the baseline JSON. A still-missing reference is a failure below, not a silent
# pass -- otherwise the benchmark would report PASS having done no image comparison.
ref_png = Path(baseline.get("accuracy", {}).get("reference_png", ""))
psnr = _psnr(ref_png, args._image_out) if ref_png.exists() else float("nan")
if not ref_png.is_file():
ref_png = baseline_path.parent / "reference.png"
psnr = _psnr(ref_png, args._image_out) if ref_png.is_file() else float("nan")
base_gen = baseline.get("generate", {})
cur_gen = metrics["generate"]
@ -394,7 +401,9 @@ def _compare(args: argparse.Namespace) -> int:
)
if base_peak and cur_peak and vram_reg > args.max_vram_regression:
failures.append(f"peak VRAM +{vram_reg * 100:.1f}% > {args.max_vram_regression * 100:.0f}%")
if not math.isnan(psnr) and psnr < args.min_psnr:
if math.isnan(psnr):
failures.append("PSNR reference image missing; cannot verify output quality")
elif psnr < args.min_psnr:
failures.append(f"PSNR {psnr:.2f}dB < {args.min_psnr:.1f}dB (output changed)")
if failures: