modify ip_adapter's CrossAttentionAdapters injection logic

src/refiners/foundationals/latent_diffusion/image_prompt.py

@@ -282,28 +282,44 @@ class CrossAttentionAdapter(fl.Chain, Adapter[fl.Attention]):
         target: fl.Attention,
         scale: float = 1.0,
     ) -> None:
-        self._scale = scale
         with self.setup_adapter(target):
-            clone = target.structural_copy()
-            scaled_dot_product = clone.ensure_find(ScaledDotProductAttention)
-            image_cross_attention = ImageCrossAttention(
-                text_cross_attention=clone,
-                scale=self.scale,
+            super().__init__(target)
+
+        self._image_cross_attention = [
+            ImageCrossAttention(
+                text_cross_attention=target,
+                scale=scale,
             )
-            clone.replace(
-                old_module=scaled_dot_product,
+        ]
+
+    def inject(self, parent: fl.Chain | None = None) -> "CrossAttentionAdapter":
+        sdpa = self.target.ensure_find(ScaledDotProductAttention)
+        # replace the spda by a Sum of itself and the ImageCrossAttention
+        self.target.replace(
+            old_module=sdpa,
             new_module=fl.Sum(
-                    scaled_dot_product,
-                    image_cross_attention,
+                sdpa,
+                self.image_cross_attention,
             ),
         )
-            super().__init__(
-                clone,
+        return super().inject(parent)
+
+    def eject(self) -> None:
+        # find the parent of the ImageCrossAttention (Sum)
+        parent = self.target.ensure_find_parent(self.image_cross_attention)
+        # unlink the ImageCrossAttention from its parent
+        parent.remove(self.image_cross_attention)
+        # replace the Sum by the original ScaledDotProductAttention
+        sdpa = parent.layer("ScaledDotProductAttention", ScaledDotProductAttention)
+        self.target.replace(
+            old_module=parent,
+            new_module=sdpa,
         )
+        super().eject()
 
     @property
     def image_cross_attention(self) -> ImageCrossAttention:
-        return self.ensure_find(ImageCrossAttention)
+        return self._image_cross_attention[0]
 
     @property
     def image_key_projection(self) -> fl.Linear:
@@ -315,7 +331,7 @@ class CrossAttentionAdapter(fl.Chain, Adapter[fl.Attention]):
 
     @property
     def scale(self) -> float:
-        return self._scale
+        return self.image_cross_attention.scale
 
     @scale.setter
     def scale(self, value: float) -> None:

tests/adapters/test_ip_adapter.py

@@ -35,6 +35,10 @@ def test_inject_eject(k_unet: type[SD1UNet] | type[SDXLUNet], test_device: torch
     assert repr(unet) != initial_repr
     adapter.eject()
     assert repr(unet) == initial_repr
+    adapter.inject()
+    assert repr(unet) != initial_repr
+    adapter.eject()
+    assert repr(unet) == initial_repr
 
 
 @no_grad()