modify to attn1/attn2 only

networks/lora_control_net.py

@@ -18,7 +18,11 @@ SKIP_CONV2D = False
 # if True, only transformer_blocks are applied, and ResBlocks are not applied
 TRANSFORMER_ONLY = True  # if True, SKIP_CONV2D is ignored because conv2d is not used in transformer_blocks
 
+# Trueならattn1とattn2にのみ適用し、ffなどには適用しない / if True, apply only to attn1 and attn2, not to ff etc.
+ATTN1_2_ONLY = True
+
 # Trueならattn1やffなどにのみ適用し、attn2などには適用しない / if True, apply only to attn1 and ff, not to attn2
+# ATTN1_2_ONLYと同時にTrueにできない / cannot be True at the same time as ATTN1_2_ONLY
 ATTN1_ETC_ONLY = False  # True
 
 # transformer_blocksの最大インデックス。Noneなら全てのtransformer_blocksに適用
@@ -203,6 +207,10 @@ class LoRAControlNet(torch.nn.Module):
                             if "emb_layers" in lora_name or ("attn2" in lora_name and ("to_k" in lora_name or "to_v" in lora_name)):
                                 continue
 
+                            if ATTN1_2_ONLY:
+                                if not ("attn1" in lora_name or "attn2" in lora_name):
+                                    continue
+
                             if ATTN1_ETC_ONLY:
                                 if "proj_out" in lora_name:
                                     pass
@@ -368,7 +376,7 @@ if __name__ == "__main__":
     unet.to("cuda").to(torch.float16)
 
     print("create LoRA controlnet")
-    control_net = LoRAControlNet(unet, 64, 16, 1)
+    control_net = LoRAControlNet(unet, 64, 32, 1)
     control_net.apply_to()
     control_net.to("cuda")
 

sdxl_train_lora_control_net.py

@@ -325,7 +325,7 @@ def train(args):
 
         accelerator.print(f"\nsaving checkpoint: {ckpt_file}")
         sai_metadata = train_util.get_sai_model_spec(None, args, True, True, False)
-        sai_metadata["modelspec.architecture"] = sai_model_spec.ARCH_SD_XL_V1_BASE + "/lora-control-net"
+        sai_metadata["modelspec.architecture"] = sai_model_spec.ARCH_SD_XL_V1_BASE + "/control-net-llite"
 
         unwrapped_nw.save_weights(ckpt_file, save_dtype, sai_metadata)
         if args.huggingface_repo_id is not None: