Fix ONNX/Olive.

modules/onnx_impl/pipelines/__init__.py

@@ -379,17 +379,17 @@ def preprocess(self, p: StableDiffusionProcessing):
         }
         in_dir = out_dir
 
-        if shared.opts.cuda_compile_backend == "olive-ai":
+        if shared.opts.olive_enable:
             submodels_for_olive = []
 
-            if "Text Encoder" in shared.opts.cuda_compile:
+            if "Text Encoder" in shared.opts.olive_submodels:
                 if not self.is_refiner:
                     submodels_for_olive.append("text_encoder")
                 if self._is_sdxl:
                     submodels_for_olive.append("text_encoder_2")
-            if "Model" in shared.opts.cuda_compile:
+            if "Model" in shared.opts.olive_submodels:
                 submodels_for_olive.append("unet")
-            if "VAE" in shared.opts.cuda_compile:
+            if "VAE" in shared.opts.olive_submodels:
                 submodels_for_olive.append("vae_encoder")
                 submodels_for_olive.append("vae_decoder")
 

modules/onnx_impl/ui.py

@@ -38,7 +38,7 @@ def create_ui():
                 ep_log = gr.HTML("")
                 ep_install.click(fn=install_execution_provider, inputs=[ep_checkbox], outputs=[ep_log])
 
-            if opts.cuda_compile_backend == "olive-ai":
+            if opts.olive_enable:
                 import olive.passes as olive_passes
                 from olive.hardware.accelerator import AcceleratorSpec, Device
                 accelerator = AcceleratorSpec(accelerator_type=Device.GPU, execution_provider=opts.onnx_execution_provider)

modules/onnx_impl/utils.py

@@ -38,8 +38,7 @@ def move_inference_session(session: ort.InferenceSession, device: torch.device):
 
 
 def check_diffusers_cache(path: os.PathLike):
-    from modules.shared import opts
-    return opts.diffusers_dir in os.path.abspath(path)
+    return False
 
 
 def check_pipeline_sdxl(cls: Type[diffusers.DiffusionPipeline]) -> bool: