Revert "fix-copies went uncaught it seems."

This reverts commit eefb302.

Author: sayakpaul

src/diffusers/pipelines/flux/pipeline_flux_controlnet.py

@@ -440,28 +440,23 @@ def prepare_ip_adapter_image_embeds(
             if not isinstance(ip_adapter_image, list):
                 ip_adapter_image = [ip_adapter_image]
 
-            if len(ip_adapter_image) != self.transformer.encoder_hid_proj.num_ip_adapters:
+            if len(ip_adapter_image) != len(self.transformer.encoder_hid_proj.image_projection_layers):
                 raise ValueError(
-                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
+                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {len(self.transformer.encoder_hid_proj.image_projection_layers)} IP Adapters."
                 )
 
-            for single_ip_adapter_image in ip_adapter_image:
+            for single_ip_adapter_image, image_proj_layer in zip(
+                ip_adapter_image, self.transformer.encoder_hid_proj.image_projection_layers
+            ):
                 single_image_embeds = self.encode_image(single_ip_adapter_image, device, 1)
+
                 image_embeds.append(single_image_embeds[None, :])
         else:
-            if not isinstance(ip_adapter_image_embeds, list):
-                ip_adapter_image_embeds = [ip_adapter_image_embeds]
-
-            if len(ip_adapter_image_embeds) != self.transformer.encoder_hid_proj.num_ip_adapters:
-                raise ValueError(
-                    f"`ip_adapter_image_embeds` must have same length as the number of IP Adapters. Got {len(ip_adapter_image_embeds)} image embeds and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
-                )
-
             for single_image_embeds in ip_adapter_image_embeds:
                 image_embeds.append(single_image_embeds)
 
         ip_adapter_image_embeds = []
-        for single_image_embeds in image_embeds:
+        for i, single_image_embeds in enumerate(image_embeds):
             single_image_embeds = torch.cat([single_image_embeds] * num_images_per_prompt, dim=0)
             single_image_embeds = single_image_embeds.to(device=device)
             ip_adapter_image_embeds.append(single_image_embeds)

src/diffusers/pipelines/flux/pipeline_flux_img2img.py

@@ -427,28 +427,23 @@ def prepare_ip_adapter_image_embeds(
             if not isinstance(ip_adapter_image, list):
                 ip_adapter_image = [ip_adapter_image]
 
-            if len(ip_adapter_image) != self.transformer.encoder_hid_proj.num_ip_adapters:
+            if len(ip_adapter_image) != len(self.transformer.encoder_hid_proj.image_projection_layers):
                 raise ValueError(
-                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
+                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {len(self.transformer.encoder_hid_proj.image_projection_layers)} IP Adapters."
                 )
 
-            for single_ip_adapter_image in ip_adapter_image:
+            for single_ip_adapter_image, image_proj_layer in zip(
+                ip_adapter_image, self.transformer.encoder_hid_proj.image_projection_layers
+            ):
                 single_image_embeds = self.encode_image(single_ip_adapter_image, device, 1)
+
                 image_embeds.append(single_image_embeds[None, :])
         else:
-            if not isinstance(ip_adapter_image_embeds, list):
-                ip_adapter_image_embeds = [ip_adapter_image_embeds]
-
-            if len(ip_adapter_image_embeds) != self.transformer.encoder_hid_proj.num_ip_adapters:
-                raise ValueError(
-                    f"`ip_adapter_image_embeds` must have same length as the number of IP Adapters. Got {len(ip_adapter_image_embeds)} image embeds and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
-                )
-
             for single_image_embeds in ip_adapter_image_embeds:
                 image_embeds.append(single_image_embeds)
 
         ip_adapter_image_embeds = []
-        for single_image_embeds in image_embeds:
+        for i, single_image_embeds in enumerate(image_embeds):
             single_image_embeds = torch.cat([single_image_embeds] * num_images_per_prompt, dim=0)
             single_image_embeds = single_image_embeds.to(device=device)
             ip_adapter_image_embeds.append(single_image_embeds)

src/diffusers/pipelines/flux/pipeline_flux_inpaint.py

@@ -432,28 +432,23 @@ def prepare_ip_adapter_image_embeds(
             if not isinstance(ip_adapter_image, list):
                 ip_adapter_image = [ip_adapter_image]
 
-            if len(ip_adapter_image) != self.transformer.encoder_hid_proj.num_ip_adapters:
+            if len(ip_adapter_image) != len(self.transformer.encoder_hid_proj.image_projection_layers):
                 raise ValueError(
-                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
+                    f"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {len(self.transformer.encoder_hid_proj.image_projection_layers)} IP Adapters."
                 )
 
-            for single_ip_adapter_image in ip_adapter_image:
+            for single_ip_adapter_image, image_proj_layer in zip(
+                ip_adapter_image, self.transformer.encoder_hid_proj.image_projection_layers
+            ):
                 single_image_embeds = self.encode_image(single_ip_adapter_image, device, 1)
+
                 image_embeds.append(single_image_embeds[None, :])
         else:
-            if not isinstance(ip_adapter_image_embeds, list):
-                ip_adapter_image_embeds = [ip_adapter_image_embeds]
-
-            if len(ip_adapter_image_embeds) != self.transformer.encoder_hid_proj.num_ip_adapters:
-                raise ValueError(
-                    f"`ip_adapter_image_embeds` must have same length as the number of IP Adapters. Got {len(ip_adapter_image_embeds)} image embeds and {self.transformer.encoder_hid_proj.num_ip_adapters} IP Adapters."
-                )
-
             for single_image_embeds in ip_adapter_image_embeds:
                 image_embeds.append(single_image_embeds)
 
         ip_adapter_image_embeds = []
-        for single_image_embeds in image_embeds:
+        for i, single_image_embeds in enumerate(image_embeds):
             single_image_embeds = torch.cat([single_image_embeds] * num_images_per_prompt, dim=0)
             single_image_embeds = single_image_embeds.to(device=device)
             ip_adapter_image_embeds.append(single_image_embeds)