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bench: --ref-downscale option — pre-shrink refs before the node (24GB OOM mitigation)

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Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Hanashi
2026-08-06 14:44:54 -04:00
parent a293d0a2c4
commit 4c2635515b
1 changed files with 24 additions and 11 deletions
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bench/minimax_bench.py
+24 -11
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@@ -85,7 +85,8 @@ def snap_length(seconds: float) -> int:
def build_graph(task, model_file, prompt, width, height, length, steps, seed,
sampler="res_multistep", scheduler="simple", image=BENCH_IMAGE,
ref_image_size="match", ref_count=1, filename_prefix="bench/run"):
ref_image_size="match", ref_count=1, ref_downscale=0.0,
filename_prefix="bench/run"):
g = {
"1": {"class_type": "UNETLoader",
"inputs": {"unet_name": model_file, "weight_dtype": "default"}},
@@ -122,15 +123,25 @@ def build_graph(task, model_file, prompt, width, height, length, steps, seed,
**common}}
elif task == "ref2v":
ref_inputs = {}
def ref_source(nid_load, fname):
g[nid_load] = {"class_type": "LoadImage", "inputs": {"image": fname}}
if not ref_downscale:
return [nid_load, 0]
nid_scale = str(int(nid_load) + 40)
g[nid_scale] = {"class_type": "ImageScaleToTotalPixels",
"inputs": {"image": [nid_load, 0],
"upscale_method": "lanczos",
"megapixels": ref_downscale,
"resolution_steps": 1}}
return [nid_scale, 0]
if ref_count <= 1:
g["10"] = {"class_type": "LoadImage", "inputs": {"image": image}}
ref_inputs["ref_images.ref_image_0"] = ["10", 0]
ref_inputs["ref_images.ref_image_0"] = ref_source("10", image)
else:
for i in range(ref_count):
nid = str(20 + i)
g[nid] = {"class_type": "LoadImage",
"inputs": {"image": BENCH_REF_SET[i % len(BENCH_REF_SET)]}}
ref_inputs[f"ref_images.ref_image_{i}"] = [nid, 0]
ref_inputs[f"ref_images.ref_image_{i}"] = ref_source(
str(20 + i), BENCH_REF_SET[i % len(BENCH_REF_SET)])
g["5"] = {"class_type": "MiniMaxH3ReferenceToVideo",
"inputs": {"clip": ["2", 0], "vae": ["3", 0], "audio_vae": ["4", 0],
"ref_image_size": ref_image_size,
@@ -173,7 +184,7 @@ def run_one(api, cfg, poll=2.0, timeout=3600):
graph = build_graph(**{k: v for k, v in cfg.items() if k in (
"task", "model_file", "prompt", "width", "height", "length", "steps", "seed",
"sampler", "scheduler", "image", "ref_image_size", "ref_count",
"filename_prefix")})
"ref_downscale", "filename_prefix")})
peak = {"vram": 0}
stop = threading.Event()
@@ -263,7 +274,7 @@ def default_prompt(task):
def make_cfg(task, model_file, width, height, seconds, steps, seed, label, warm,
sampler="res_multistep", scheduler="simple", ref_image_size="match",
ref_count=1):
ref_count=1, ref_downscale=0.0):
prompt = ref2v_prompt(ref_count) if task == "ref2v" else default_prompt(task)
return {
"label": label, "task": task, "model_file": model_file,
@@ -271,7 +282,7 @@ def make_cfg(task, model_file, width, height, seconds, steps, seed, label, warm,
"seconds": seconds, "length": snap_length(seconds), "steps": steps,
"seed": seed, "sampler": sampler, "scheduler": scheduler,
"image": BENCH_IMAGE, "ref_image_size": ref_image_size,
"ref_count": ref_count, "warm": warm,
"ref_count": ref_count, "ref_downscale": ref_downscale, "warm": warm,
"filename_prefix": f"bench/{label}",
}
@@ -395,6 +406,8 @@ def main():
ap.add_argument("--ref-image-size", default="match", choices=["match", "max"])
ap.add_argument("--ref-count", type=int, default=1,
help="number of reference images for ref2v (1-8)")
ap.add_argument("--ref-downscale", type=float, default=0.0,
help="pre-downscale refs to this many megapixels before the node (0=off)")
ap.add_argument("--label", default=None)
ap.add_argument("--prefix", default="", help="label prefix for suites, e.g. prunedint8_")
ap.add_argument("--warm", action="store_true", help="mark run as warm (model preloaded)")
@@ -423,7 +436,7 @@ def main():
cfgs = [make_cfg(args.task, model, args.width, args.height, args.seconds,
args.steps, args.seed, label, args.warm,
args.sampler, args.scheduler, args.ref_image_size,
args.ref_count)]
args.ref_count, args.ref_downscale)]
else:
ap.error("need --suite or --task")