pre calc LoRA in generating

gen_img_diffusers.py

@@ -2262,6 +2262,8 @@ def main(args):
     if args.network_module:
         networks = []
         network_default_muls = []
+        network_pre_calc=args.network_pre_calc
+
         for i, network_module in enumerate(args.network_module):
             print("import network module:", network_module)
             imported_module = importlib.import_module(network_module)
@@ -2298,11 +2300,11 @@ def main(args):
             if network is None:
                 return
 
-            mergiable = hasattr(network, "merge_to")
-            if args.network_merge and not mergiable:
+            mergeable = network.is_mergeable()
+            if args.network_merge and not mergeable:
                 print("network is not mergiable. ignore merge option.")
 
-            if not args.network_merge or not mergiable:
+            if not args.network_merge or not mergeable:
                 network.apply_to(text_encoder, unet)
                 info = network.load_state_dict(weights_sd, False)  # network.load_weightsを使うようにするとよい
                 print(f"weights are loaded: {info}")
@@ -2311,6 +2313,10 @@ def main(args):
                     network.to(memory_format=torch.channels_last)
                 network.to(dtype).to(device)
 
+                if network_pre_calc:
+                    print("backup original weights")
+                    network.backup_weights()
+
                 networks.append(network)
             else:
                 network.merge_to(text_encoder, unet, weights_sd, dtype, device)
@@ -2815,11 +2821,19 @@ def main(args):
 
             # generate
             if networks:
+                # 追加ネットワークの処理
                 shared = {}
                 for n, m in zip(networks, network_muls if network_muls else network_default_muls):
                     n.set_multiplier(m)
                     if regional_network:
                         n.set_current_generation(batch_size, num_sub_prompts, width, height, shared)
+                
+                if not regional_network and network_pre_calc:
+                    for n in networks:
+                        n.restore_weights()
+                    for n in networks:
+                        n.pre_calculation()
+                    print("pre-calculation... done")
 
             images = pipe(
                 prompts,
@@ -3204,6 +3218,7 @@ def setup_parser() -> argparse.ArgumentParser:
     )
     parser.add_argument("--network_show_meta", action="store_true", help="show metadata of network model / ネットワークモデルのメタデータを表示する")
     parser.add_argument("--network_merge", action="store_true", help="merge network weights to original model / ネットワークの重みをマージする")
+    parser.add_argument("--network_pre_calc", action="store_true", help="pre-calculate network for generation / ネットワークのあらかじめ計算して生成する")
     parser.add_argument(
         "--textual_inversion_embeddings",
         type=str,