fix(api): pass both device and session options to ORT (#38)

api/onnx_web/chain/upscale_resrgan.py

@@ -52,8 +52,8 @@ def load_resrgan(
         model = OnnxNet(
             server,
             model_file,
-            provider=device.provider,
-            sess_options=device.options,
+            provider=device.ort_provider(),
+            sess_options=device.sess_options(),
         )
     elif params.format == "pth":
         model = RRDBNet(

api/onnx_web/chain/upscale_stable_diffusion.py

@@ -34,7 +34,9 @@ def load_stable_diffusion(
             device.provider,
         )
         pipe = OnnxStableDiffusionUpscalePipeline.from_pretrained(
-            model_path, provider=device.provider, sess_options=device.options
+            model_path,
+            provider=device.ort_provider(),
+            sess_options=device.sess_options(),
         )
     else:
         logger.debug(
@@ -43,7 +45,8 @@ def load_stable_diffusion(
             device.provider,
         )
         pipe = StableDiffusionUpscalePipeline.from_pretrained(
-            model_path, provider=device.provider
+            model_path,
+            provider=device.provider,
         )
 
     server.cache.set("diffusion", cache_key, pipe)

api/onnx_web/diffusion/load.py

@@ -109,8 +109,8 @@ def load_pipeline(
             logger.debug("loading new diffusion scheduler")
             scheduler = scheduler_type.from_pretrained(
                 model,
-                provider=device.provider,
-                sess_options=device.options,
+                provider=device.ort_provider(),
+                sess_options=device.sess_options(),
                 subfolder="scheduler",
             )
 
@@ -134,15 +134,15 @@ def load_pipeline(
         logger.debug("loading new diffusion pipeline from %s", model)
         scheduler = scheduler_type.from_pretrained(
             model,
-            provider=device.provider,
-            sess_options=device.options,
+            provider=device.ort_provider(),
+            sess_options=device.sess_options(),
             subfolder="scheduler",
         )
         pipe = pipeline.from_pretrained(
             model,
             custom_pipeline=custom_pipeline,
-            provider=device.provider,
-            sess_options=device.options,
+            provider=device.ort_provider(),
+            sess_options=device.sess_options(),
             revision="onnx",
             safety_checker=None,
             scheduler=scheduler,

api/onnx_web/onnx/onnx_net.py

@@ -3,7 +3,7 @@ from typing import Any, Optional
 
 import numpy as np
 import torch
-from onnxruntime import InferenceSession
+from onnxruntime import InferenceSession, SessionOptions
 
 from ..utils import ServerContext
 
@@ -47,7 +47,7 @@ class OnnxNet:
         server: ServerContext,
         model: str,
         provider: str = "DmlExecutionProvider",
-        sess_options: Optional[dict] = None,
+        sess_options: Optional[SessionOptions] = None,
     ) -> None:
         model_path = path.join(server.model_path, model)
         self.session = InferenceSession(

api/onnx_web/params.py

@@ -1,4 +1,5 @@
 from enum import IntEnum
+from onnxruntime import SessionOptions
 from typing import Any, Dict, Literal, Optional, Tuple, Union
 
 
@@ -79,6 +80,15 @@ class DeviceParams:
     def __str__(self) -> str:
         return "%s - %s (%s)" % (self.device, self.provider, self.options)
 
+    def ort_provider(self) -> Tuple[str, Any]:
+        if self.options is None:
+            return self.provider
+        else:
+            return (self.provider, self.options)
+
+    def sess_options(self) -> SessionOptions:
+        return SessionOptions()
+
     def torch_device(self) -> str:
         if self.device.startswith("cuda"):
             return self.device