Support more Wan loras (VACE) (#11726)

update

src/diffusers/loaders/lora_conversion_utils.py

@@ -1596,7 +1596,10 @@ def _convert_non_diffusers_wan_lora_to_diffusers(state_dict):
     converted_state_dict = {}
     original_state_dict = {k[len("diffusion_model.") :]: v for k, v in state_dict.items()}
 
-    num_blocks = len({k.split("blocks.")[1].split(".")[0] for k in original_state_dict if "blocks." in k})
+    block_numbers = {int(k.split(".")[1]) for k in original_state_dict if k.startswith("blocks.")}
+    min_block = min(block_numbers)
+    max_block = max(block_numbers)
+
     is_i2v_lora = any("k_img" in k for k in original_state_dict) and any("v_img" in k for k in original_state_dict)
     lora_down_key = "lora_A" if any("lora_A" in k for k in original_state_dict) else "lora_down"
     lora_up_key = "lora_B" if any("lora_B" in k for k in original_state_dict) else "lora_up"
@@ -1622,45 +1625,57 @@ def _convert_non_diffusers_wan_lora_to_diffusers(state_dict):
     # For the `diff_b` keys, we treat them as lora_bias.
     # https://huggingface.co/docs/peft/main/en/package_reference/lora#peft.LoraConfig.lora_bias
 
-    for i in range(num_blocks):
+    for i in range(min_block, max_block + 1):
         # Self-attention
         for o, c in zip(["q", "k", "v", "o"], ["to_q", "to_k", "to_v", "to_out.0"]):
-            converted_state_dict[f"blocks.{i}.attn1.{c}.lora_A.weight"] = original_state_dict.pop(
-                f"blocks.{i}.self_attn.{o}.{lora_down_key}.weight"
-            )
-            converted_state_dict[f"blocks.{i}.attn1.{c}.lora_B.weight"] = original_state_dict.pop(
-                f"blocks.{i}.self_attn.{o}.{lora_up_key}.weight"
-            )
-            if f"blocks.{i}.self_attn.{o}.diff_b" in original_state_dict:
-                converted_state_dict[f"blocks.{i}.attn1.{c}.lora_B.bias"] = original_state_dict.pop(
-                    f"blocks.{i}.self_attn.{o}.diff_b"
-                )
+            original_key = f"blocks.{i}.self_attn.{o}.{lora_down_key}.weight"
+            converted_key = f"blocks.{i}.attn1.{c}.lora_A.weight"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+            original_key = f"blocks.{i}.self_attn.{o}.{lora_up_key}.weight"
+            converted_key = f"blocks.{i}.attn1.{c}.lora_B.weight"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+            original_key = f"blocks.{i}.self_attn.{o}.diff_b"
+            converted_key = f"blocks.{i}.attn1.{c}.lora_B.bias"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
 
         # Cross-attention
         for o, c in zip(["q", "k", "v", "o"], ["to_q", "to_k", "to_v", "to_out.0"]):
-            converted_state_dict[f"blocks.{i}.attn2.{c}.lora_A.weight"] = original_state_dict.pop(
-                f"blocks.{i}.cross_attn.{o}.{lora_down_key}.weight"
-            )
-            converted_state_dict[f"blocks.{i}.attn2.{c}.lora_B.weight"] = original_state_dict.pop(
-                f"blocks.{i}.cross_attn.{o}.{lora_up_key}.weight"
-            )
-            if f"blocks.{i}.cross_attn.{o}.diff_b" in original_state_dict:
-                converted_state_dict[f"blocks.{i}.attn2.{c}.lora_B.bias"] = original_state_dict.pop(
-                    f"blocks.{i}.cross_attn.{o}.diff_b"
-                )
+            original_key = f"blocks.{i}.cross_attn.{o}.{lora_down_key}.weight"
+            converted_key = f"blocks.{i}.attn2.{c}.lora_A.weight"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+            original_key = f"blocks.{i}.cross_attn.{o}.{lora_up_key}.weight"
+            converted_key = f"blocks.{i}.attn2.{c}.lora_B.weight"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+            original_key = f"blocks.{i}.cross_attn.{o}.diff_b"
+            converted_key = f"blocks.{i}.attn2.{c}.lora_B.bias"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
 
         if is_i2v_lora:
             for o, c in zip(["k_img", "v_img"], ["add_k_proj", "add_v_proj"]):
-                converted_state_dict[f"blocks.{i}.attn2.{c}.lora_A.weight"] = original_state_dict.pop(
-                    f"blocks.{i}.cross_attn.{o}.{lora_down_key}.weight"
-                )
-                converted_state_dict[f"blocks.{i}.attn2.{c}.lora_B.weight"] = original_state_dict.pop(
-                    f"blocks.{i}.cross_attn.{o}.{lora_up_key}.weight"
-                )
-                if f"blocks.{i}.cross_attn.{o}.diff_b" in original_state_dict:
-                    converted_state_dict[f"blocks.{i}.attn2.{c}.lora_B.bias"] = original_state_dict.pop(
-                        f"blocks.{i}.cross_attn.{o}.diff_b"
-                    )
+                original_key = f"blocks.{i}.cross_attn.{o}.{lora_down_key}.weight"
+                converted_key = f"blocks.{i}.attn2.{c}.lora_A.weight"
+                if original_key in original_state_dict:
+                    converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+                original_key = f"blocks.{i}.cross_attn.{o}.{lora_up_key}.weight"
+                converted_key = f"blocks.{i}.attn2.{c}.lora_B.weight"
+                if original_key in original_state_dict:
+                    converted_state_dict[converted_key] = original_state_dict.pop(original_key)
+
+                original_key = f"blocks.{i}.cross_attn.{o}.diff_b"
+                converted_key = f"blocks.{i}.attn2.{c}.lora_B.bias"
+                if original_key in original_state_dict:
+                    converted_state_dict[converted_key] = original_state_dict.pop(original_key)
 
         # FFN
         for o, c in zip(["ffn.0", "ffn.2"], ["net.0.proj", "net.2"]):
@@ -1674,10 +1689,10 @@ def _convert_non_diffusers_wan_lora_to_diffusers(state_dict):
             if original_key in original_state_dict:
                 converted_state_dict[converted_key] = original_state_dict.pop(original_key)
 
-            if f"blocks.{i}.{o}.diff_b" in original_state_dict:
-                converted_state_dict[f"blocks.{i}.ffn.{c}.lora_B.bias"] = original_state_dict.pop(
-                    f"blocks.{i}.{o}.diff_b"
-                )
+            original_key = f"blocks.{i}.{o}.diff_b"
+            converted_key = f"blocks.{i}.ffn.{c}.lora_B.bias"
+            if original_key in original_state_dict:
+                converted_state_dict[converted_key] = original_state_dict.pop(original_key)
 
     # Remaining.
     if original_state_dict: