update

Author: sayakpaul

src/diffusers/loaders/lora_base.py

@@ -465,7 +465,6 @@ class LoraBaseMixin:
     """Utility class for handling LoRAs."""
 
     _lora_loadable_modules = []
-    _merged_adapters = set()
 
     def load_lora_weights(self, **kwargs):
         raise NotImplementedError("`load_lora_weights()` is not implemented.")
@@ -505,6 +504,12 @@ def _best_guess_weight_name(cls, *args, **kwargs):
         deprecate("_best_guess_weight_name", "0.35.0", deprecation_message)
         return _best_guess_weight_name(*args, **kwargs)
 
+    @property
+    def _merged_adapters(self):
+        if "_merged_adapters" not in self.__dict__:
+            self.__dict__["_merged_adapters"] = set()
+        return self.__dict__["_merged_adapters"]
+
     def unload_lora_weights(self):
         """
         Unloads the LoRA parameters.

tests/lora/utils.py

@@ -877,11 +877,15 @@ def test_simple_inference_with_text_denoiser_lora_unfused(
             pipe, denoiser = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config)
 
             pipe.fuse_lora(components=self.pipeline_class._lora_loadable_modules)
-            assert pipe.num_fused_loras == 1, pipe.num_fused_loras
+            self.assertTrue(
+                pipe.num_fused_loras == 1, pipe.num_fused_loras, f"{pipe.num_fused_loras=}, {pipe.fused_loras=}"
+            )
             output_fused_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
 
             pipe.unfuse_lora(components=self.pipeline_class._lora_loadable_modules)
-            assert pipe.num_fused_loras == 0, pipe.num_fused_loras
+            self.assertTrue(
+                pipe.num_fused_loras == 0, pipe.num_fused_loras, f"{pipe.num_fused_loras=}, {pipe.fused_loras=}"
+            )
             output_unfused_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
 
             # unloading should remove the LoRA layers
@@ -1703,7 +1707,7 @@ def test_lora_scale_kwargs_match_fusion(self, expected_atol: float = 1e-3, expec
                     adapter_names=["adapter-1"],
                     lora_scale=lora_scale,
                 )
-                assert pipe.num_fused_loras == 1, pipe.num_fused_loras
+                self.assertTrue(pipe.num_fused_loras == 1, f"{pipe.num_fused_loras=}, {pipe.fused_loras=}")
 
                 outputs_lora_1_fused = pipe(**inputs, generator=torch.manual_seed(0))[0]