support tokenizer caching for offline training/gen

gen_img_diffusers.py

@@ -80,6 +80,7 @@ from PIL import Image
 from PIL.PngImagePlugin import PngInfo
 
 import library.model_util as model_util
+import library.train_util as train_util
 import tools.original_control_net as original_control_net
 from tools.original_control_net import ControlNetInfo
 
@@ -1963,10 +1964,7 @@ def main(args):
   # tokenizerを読み込む
   print("loading tokenizer")
   if use_stable_diffusion_format:
-    if args.v2:
-      tokenizer = CLIPTokenizer.from_pretrained(V2_STABLE_DIFFUSION_PATH, subfolder="tokenizer")
-    else:
-      tokenizer = CLIPTokenizer.from_pretrained(TOKENIZER_PATH)  # , model_max_length=max_token_length + 2)
+    tokenizer = train_util.load_tokenizer(args)
 
   # schedulerを用意する
   sched_init_args = {}
@@ -2715,6 +2713,8 @@ if __name__ == '__main__':
   parser.add_argument("--ckpt", type=str, default=None, help="path to checkpoint of model / モデルのcheckpointファイルまたはディレクトリ")
   parser.add_argument("--vae", type=str, default=None,
                       help="path to checkpoint of vae to replace / VAEを入れ替える場合、VAEのcheckpointファイルまたはディレクトリ")
+  parser.add_argument("--tokenizer_cache_dir", type=str, default=None,
+                      help="directory for caching Tokenizer (for offline training) / Tokenizerをキャッシュするディレクトリ（ネット接続なしでの学習のため）")
   # parser.add_argument("--replace_clip_l14_336", action='store_true',
   #                     help="Replace CLIP (Text Encoder) to l/14@336 / CLIP(Text Encoder)をl/14@336に入れ替える")
   parser.add_argument("--seed", type=int, default=None,