fix(api): avoid loading encoder twice when using LoRAs and inversions…

… together
ssube · Mar 18, 2023 · af326a7 · af326a7
1 parent 9f9b73b
commit af326a7
Showing 1 changed file with 8 additions and 6 deletions.
diff --git a/api/onnx_web/diffusers/load.py b/api/onnx_web/diffusers/load.py
@@ -236,14 +236,16 @@ def load_pipeline(
                 list(zip(inversion_models, inversion_weights, inversion_names)),
             )
 
+            components["tokenizer"] = tokenizer
+
             # should be pretty small and should not need external data
-            components["text_encoder"] = OnnxRuntimeModel(
-                OnnxRuntimeModel.load_model(
-                    text_encoder.SerializeToString(),
-                    provider=device.ort_provider(),
+            if loras is None or len(loras) == 0:
+                components["text_encoder"] = OnnxRuntimeModel(
+                    OnnxRuntimeModel.load_model(
+                        text_encoder.SerializeToString(),
+                        provider=device.ort_provider(),
+                    )
                 )
-            )
-            components["tokenizer"] = tokenizer
 
         # test LoRA blending
         if loras is not None and len(loras) > 0: