Add comment

gen_img_diffusers.py

@@ -1845,12 +1845,12 @@ def main(args):
     text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(args.v2, args.ckpt)
   else:
     print("load Diffusers pretrained models")
-    pipe = StableDiffusionPipeline.from_pretrained(args.ckpt, safety_checker=None, torch_dtype=dtype)
-    text_encoder = pipe.text_encoder
-    vae = pipe.vae
-    unet = pipe.unet
-    tokenizer = pipe.tokenizer
-    del pipe
+    loading_pipe = StableDiffusionPipeline.from_pretrained(args.ckpt, safety_checker=None, torch_dtype=dtype)
+    text_encoder = loading_pipe.text_encoder
+    vae = loading_pipe.vae
+    unet = loading_pipe.unet
+    tokenizer = loading_pipe.tokenizer
+    del loading_pipe
 
   # VAEを読み込む
   if args.vae is not None:

train_network.py

@@ -1,3 +1,6 @@
+from diffusers.optimization import SchedulerType, TYPE_TO_SCHEDULER_FUNCTION
+from torch.optim import Optimizer
+from typing import Optional, Union
 import importlib
 import argparse
 import gc
@@ -40,9 +43,6 @@ def generate_step_logs(args: argparse.Namespace, current_loss, avr_loss, lr_sche
 # Which is a newer release of diffusers than currently packaged with sd-scripts
 # This code can be removed when newer diffusers version (v0.12.1 or greater) is tested and implemented to sd-scripts
 
-from typing import Optional, Union
-from torch.optim import Optimizer
-from diffusers.optimization import SchedulerType, TYPE_TO_SCHEDULER_FUNCTION
 
 def get_scheduler_fix(
     name: Union[str, SchedulerType],
@@ -135,7 +135,7 @@ def train(args):
     train_util.debug_dataset(train_dataset)
     return
   if len(train_dataset) == 0:
-    print("No data found. Please verify arguments / 画像がありません。引数指定を確認してください")
+    print("No data found. Please verify arguments (train_data_dir must be the parent of folders with images) / 画像がありません。引数指定を確認してください（train_data_dirには画像があるフォルダではなく、画像があるフォルダの親フォルダを指定する必要があります）")
     return
 
   # acceleratorを準備する