[LoRA] fix cross_attention_kwargs problems and tighten tests (#7388)

* debugging

* let's see the numbers

* let's see the numbers

* let's see the numbers

* restrict tolerance.

* increase inference steps.

* shallow copy of cross_attentionkwargs

* remove print

src/diffusers/models/unets/unet_2d_condition.py

@@ -1178,6 +1178,7 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin,
         # we're popping the `scale` instead of getting it because otherwise `scale` will be propagated
         # to the internal blocks and will raise deprecation warnings. this will be confusing for our users.
         if cross_attention_kwargs is not None:
+            cross_attention_kwargs = cross_attention_kwargs.copy()
             lora_scale = cross_attention_kwargs.pop("scale", 1.0)
         else:
             lora_scale = 1.0

tests/lora/test_lora_layers_peft.py

@@ -158,7 +158,7 @@ class PeftLoraLoaderMixinTests:
 
         pipeline_inputs = {
             "prompt": "A painting of a squirrel eating a burger",
-            "num_inference_steps": 2,
+            "num_inference_steps": 5,
             "guidance_scale": 6.0,
             "output_type": "np",
         }
@@ -589,7 +589,7 @@ class PeftLoraLoaderMixinTests:
                 **inputs, generator=torch.manual_seed(0), cross_attention_kwargs={"scale": 0.5}
             ).images
             self.assertTrue(
-                not np.allclose(output_lora, output_lora_scale, atol=1e-3, rtol=1e-3),
+                not np.allclose(output_lora, output_lora_scale, atol=1e-4, rtol=1e-4),
                 "Lora + scale should change the output",
             )
 
@@ -1300,6 +1300,11 @@ class StableDiffusionLoRATests(PeftLoraLoaderMixinTests, unittest.TestCase):
         pipe.load_lora_weights(lora_id)
         pipe = pipe.to("cuda")
 
+        self.assertTrue(
+            self.check_if_lora_correctly_set(pipe.unet),
+            "Lora not correctly set in UNet",
+        )
+
         self.assertTrue(
             self.check_if_lora_correctly_set(pipe.text_encoder),
             "Lora not correctly set in text encoder 2",