Fixed the CICD for diffusers

examples/diffusers/quantization/diffusion_trt.py

@@ -105,7 +105,11 @@ def main():
 
     image_name = args.save_image_as if args.save_image_as else f"{args.model}.png"
 
-    pipe = PipelineManager.create_pipeline_from(MODEL_ID[args.model], dtype_map[args.model_dtype])
+    pipe = PipelineManager.create_pipeline_from(
+        MODEL_ID[args.model],
+        dtype_map[args.model_dtype],
+        override_model_path=args.override_model_path,
+    )
 
     # Save the backbone of the pipeline and move it to the GPU
     add_embedding = None

examples/diffusers/quantization/quantize.py

@@ -309,7 +309,9 @@ def __init__(self, config: ModelConfig, logger: logging.Logger):
 
     @staticmethod
     def create_pipeline_from(
-        model_type: ModelType, torch_dtype: torch.dtype = torch.bfloat16
+        model_type: ModelType,
+        torch_dtype: torch.dtype = torch.bfloat16,
+        override_model_path: str | None = None,
     ) -> DiffusionPipeline:
         """
         Create and return an appropriate pipeline based on configuration.
@@ -321,7 +323,9 @@ def create_pipeline_from(
             ValueError: If model type is unsupported
         """
         try:
-            model_id = MODEL_REGISTRY[model_type]
+            model_id = (
+                MODEL_REGISTRY[model_type] if override_model_path is None else override_model_path
+            )
             if model_type == ModelType.SD3_MEDIUM:
                 pipe = StableDiffusion3Pipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
             elif model_type in [ModelType.FLUX_DEV, ModelType.FLUX_SCHNELL]:

examples/diffusers/quantization/requirements.txt

@@ -1,4 +1,5 @@
 cuda-python
+diffusers<=0.34.0
 nvtx
 onnx_graphsurgeon
 opencv-python>=4.8.1.78,<4.12.0.88