[LoRA] Clean Kohya conversion utils (#7374)

* clean up the kohya_conversion utility

* state dict assignment

src/diffusers/loaders/lora_conversion_utils.py

@@ -198,46 +198,13 @@ def _convert_kohya_lora_to_diffusers(state_dict, unet_name="unet", text_encoder_
                 unet_state_dict[diffusers_name] = state_dict.pop(key)
                 unet_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
 
-        elif lora_name.startswith("lora_te_"):
-            diffusers_name = key.replace("lora_te_", "").replace("_", ".")
-            diffusers_name = diffusers_name.replace("text.model", "text_model")
-            diffusers_name = diffusers_name.replace("self.attn", "self_attn")
-            diffusers_name = diffusers_name.replace("q.proj.lora", "to_q_lora")
-            diffusers_name = diffusers_name.replace("k.proj.lora", "to_k_lora")
-            diffusers_name = diffusers_name.replace("v.proj.lora", "to_v_lora")
-            diffusers_name = diffusers_name.replace("out.proj.lora", "to_out_lora")
-            if "self_attn" in diffusers_name:
-                te_state_dict[diffusers_name] = state_dict.pop(key)
-                te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
-            elif "mlp" in diffusers_name:
-                # Be aware that this is the new diffusers convention and the rest of the code might
-                # not utilize it yet.
-                diffusers_name = diffusers_name.replace(".lora.", ".lora_linear_layer.")
-                te_state_dict[diffusers_name] = state_dict.pop(key)
-                te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
-
-        # (sayakpaul): Duplicate code. Needs to be cleaned.
-        elif lora_name.startswith("lora_te1_"):
-            diffusers_name = key.replace("lora_te1_", "").replace("_", ".")
-            diffusers_name = diffusers_name.replace("text.model", "text_model")
-            diffusers_name = diffusers_name.replace("self.attn", "self_attn")
-            diffusers_name = diffusers_name.replace("q.proj.lora", "to_q_lora")
-            diffusers_name = diffusers_name.replace("k.proj.lora", "to_k_lora")
-            diffusers_name = diffusers_name.replace("v.proj.lora", "to_v_lora")
-            diffusers_name = diffusers_name.replace("out.proj.lora", "to_out_lora")
-            if "self_attn" in diffusers_name:
-                te_state_dict[diffusers_name] = state_dict.pop(key)
-                te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
-            elif "mlp" in diffusers_name:
-                # Be aware that this is the new diffusers convention and the rest of the code might
-                # not utilize it yet.
-                diffusers_name = diffusers_name.replace(".lora.", ".lora_linear_layer.")
-                te_state_dict[diffusers_name] = state_dict.pop(key)
-                te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
+        elif lora_name.startswith(("lora_te_", "lora_te1_", "lora_te2_")):
+            if lora_name.startswith(("lora_te_", "lora_te1_")):
+                key_to_replace = "lora_te_" if lora_name.startswith("lora_te_") else "lora_te1_"
+            else:
+                key_to_replace = "lora_te2_"
 
-        # (sayakpaul): Duplicate code. Needs to be cleaned.
-        elif lora_name.startswith("lora_te2_"):
-            diffusers_name = key.replace("lora_te2_", "").replace("_", ".")
+            diffusers_name = key.replace(key_to_replace, "").replace("_", ".")
             diffusers_name = diffusers_name.replace("text.model", "text_model")
             diffusers_name = diffusers_name.replace("self.attn", "self_attn")
             diffusers_name = diffusers_name.replace("q.proj.lora", "to_q_lora")
@@ -245,14 +212,22 @@ def _convert_kohya_lora_to_diffusers(state_dict, unet_name="unet", text_encoder_
             diffusers_name = diffusers_name.replace("v.proj.lora", "to_v_lora")
             diffusers_name = diffusers_name.replace("out.proj.lora", "to_out_lora")
             if "self_attn" in diffusers_name:
-                te2_state_dict[diffusers_name] = state_dict.pop(key)
-                te2_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
+                if lora_name.startswith(("lora_te_", "lora_te1_")):
+                    te_state_dict[diffusers_name] = state_dict.pop(key)
+                    te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
+                else:
+                    te2_state_dict[diffusers_name] = state_dict.pop(key)
+                    te2_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
             elif "mlp" in diffusers_name:
                 # Be aware that this is the new diffusers convention and the rest of the code might
                 # not utilize it yet.
                 diffusers_name = diffusers_name.replace(".lora.", ".lora_linear_layer.")
-                te2_state_dict[diffusers_name] = state_dict.pop(key)
-                te2_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
+                if lora_name.startswith(("lora_te_", "lora_te1_")):
+                    te_state_dict[diffusers_name] = state_dict.pop(key)
+                    te_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
+                else:
+                    te2_state_dict[diffusers_name] = state_dict.pop(key)
+                    te2_state_dict[diffusers_name.replace(".down.", ".up.")] = state_dict.pop(lora_name_up)
 
         # Rename the alphas so that they can be mapped appropriately.
         if lora_name_alpha in state_dict: