test half precision on all diffusion models

api/launch.sh

@@ -21,7 +21,9 @@ python3 -m onnx_web.convert \
   --diffusion \
   --upscaling \
   --correction \
-  --token=${HF_TOKEN:-}
+  --extras=${ONNX_WEB_EXTRA_MODELS:-extras.json} \
+  --token=${HF_TOKEN:-} \
+  --half
 
 echo "Launching API server..."
 flask --app='onnx_web.main:run' run --host=0.0.0.0

api/onnx_web/chain/upscale_stable_diffusion.py

@@ -40,6 +40,7 @@ def load_stable_diffusion(
             model_path,
             provider=device.ort_provider(),
             sess_options=device.sess_options(),
+            torch_dtype=torch.float16,
         )
     else:
         logger.debug(
@@ -50,6 +51,7 @@ def load_stable_diffusion(
         pipe = StableDiffusionUpscalePipeline.from_pretrained(
             model_path,
             provider=device.provider,
+            torch_dtype=torch.float16,
         )
 
     if not server.show_progress:

api/onnx_web/diffusion/load.py

@@ -3,6 +3,7 @@ from os import path
 from typing import Any, Optional, Tuple
 
 import numpy as np
+import torch
 from diffusers import (
     DDIMScheduler,
     DDPMScheduler,
@@ -164,6 +165,7 @@ def load_pipeline(
                 provider=device.ort_provider(),
                 sess_options=device.sess_options(),
                 subfolder="scheduler",
+                torch_dtype=torch.float16,
             )
 
             if device is not None and hasattr(scheduler, "to"):