AsianRealistic: load in fp32 to fix NaN rainbow-noise output (#22)

- AsianRealistic: load in fp32 to fix NaN rainbow-noise output (6e5f94eee0d23e5fc79c3417b1fb394a78d2b965)


Co-authored-by: pormungtailaw <pormungtai@users.noreply.huggingface.co>

models.json

@@ -9,7 +9,7 @@
       "type": "checkpoint",
       "repo_id": "stablediffusionapi/asianrealisticsdlifechias",
       "single_file_url": null,
-      "vae": "stabilityai/sd-vae-ft-mse",
+      "dtype": "fp32",
       "preview": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9c67da8b-5e57-413c-a5ca-135f5ed9af18/width=450/1743066.jpeg",
       "trigger": "",
       "clip_skip": 2,

pipeline_manager.py

@@ -201,27 +201,30 @@ def _build_base_pipeline(cfg):
     """Construct the txt2img pipeline for a model config (on CPU)."""
     base = cfg["base"]
     common = dict(token=HF_TOKEN)
+    # Some checkpoint merges overflow to NaN in fp16 (rainbow-noise output);
+    # such models set "dtype": "fp32" in the registry.
+    dt = torch.float32 if cfg.get("dtype") == "fp32" else DTYPE_SD
 
     if base == "sd15":
         from diffusers import StableDiffusionPipeline
         if cfg.get("single_file_url"):
             local = _download_url(cfg["single_file_url"])
             pipe = StableDiffusionPipeline.from_single_file(
-                local, torch_dtype=DTYPE_SD, safety_checker=None
+                local, torch_dtype=dt, safety_checker=None
             )
         else:
             pipe = StableDiffusionPipeline.from_pretrained(
-                cfg["repo_id"], torch_dtype=DTYPE_SD, safety_checker=None, **common
+                cfg["repo_id"], torch_dtype=dt, safety_checker=None, **common
             )
 
     elif base == "sdxl":
         from diffusers import StableDiffusionXLPipeline
         if cfg.get("single_file_url"):
             local = _download_url(cfg["single_file_url"])
-            pipe = StableDiffusionXLPipeline.from_single_file(local, torch_dtype=DTYPE_SD)
+            pipe = StableDiffusionXLPipeline.from_single_file(local, torch_dtype=dt)
         else:
             pipe = StableDiffusionXLPipeline.from_pretrained(
-                cfg["repo_id"], torch_dtype=DTYPE_SD, **common
+                cfg["repo_id"], torch_dtype=dt, **common
             )
 
     elif base == "flux":
@@ -262,11 +265,10 @@ def _build_base_pipeline(cfg):
         except Exception as e:  # noqa
             print(f"[lora] fuse skipped: {e}")
 
-    # Optional VAE override — some merged checkpoints ship a broken fp16 VAE that
-    # decodes to rainbow noise; a known-good VAE fixes it.
+    # Optional VAE override (known-good VAE for models with a broken one).
     if cfg.get("vae"):
         from diffusers import AutoencoderKL
-        pipe.vae = AutoencoderKL.from_pretrained(cfg["vae"], torch_dtype=DTYPE_SD)
+        pipe.vae = AutoencoderKL.from_pretrained(cfg["vae"], torch_dtype=dt)
 
     # SD1.5 / SDXL community checkpoints are tuned for the Euler Ancestral sampler;
     # it matches the look people get in A1111 / ComfyUI far better than the default.