RetardScript v1.13
If something not werks or not werks correctly, leave a message here:
https://github.com/anon-1337/LoRA-scripts/issues

Checking paths...
Calculating number of images in folders
Training images:
        Training: 12 repeats * 11 images = 132
Training images number with repeats: 132
Using number of training images to calculate total training steps
Number of epochs: 10
Training batch size: 1
Total training steps: 132 / 1 * 10 = 1320
Stable Diffusion 1.x checkpoint
Launching script with parameters:
 --network_module = networks.lora
 --train_data_dir = "A:\LoraTraining\sd-scripts\training_data\img"
 --reg_data_dir = "A:\LoraTraining\sd-scripts\training_data\reg"
 --output_dir = "A:\LoraTraining\sd-scripts\training_data\outputs"
 --output_name = ""
 --pretrained_model_name_or_path = "A:\LoraTraining\novelai.ckpt"
 --vae = "A:\LoraTraining\"
 --max_train_epochs = 10
 --train_batch_size = 1
 --resolution = 512
 --save_every_n_epochs = 1
 --save_last_n_epochs = 999
 --clip_skip = 2
 --learning_rate = 0.0001
 --lr_scheduler = cosine_with_restarts
 --lr_warmup_steps = 0
 --network_dim = 128
 --seed = 1613203403
 --shuffle_caption
 --keep_tokens = 0
 --max_data_loader_n_workers = 8
 --mixed_precision = fp16
 --save_precision = fp16
 --caption_extension = ".txt"
 --prior_loss_weight = 1
 --enable_bucket
 --min_bucket_reso = 256
 --max_bucket_reso = 1024
 --use_8bit_adam
 --xformers
 --save_model_as = safetensors
 --cache_latents

prepare tokenizer
Use DreamBooth method.
prepare train images.
found directory 12_Training contains 11 image files
132 train images with repeating.
prepare reg images.
0 reg images.
no regularization images / 正則化画像が見つかりませんでした
loading image sizes.
100%|████████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<00:00, 1575.68it/s]
make buckets
number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）
bucket 0: resolution (256, 832), count: 0
bucket 1: resolution (256, 896), count: 0
bucket 2: resolution (256, 960), count: 0
bucket 3: resolution (256, 1024), count: 0
bucket 4: resolution (320, 704), count: 12
bucket 5: resolution (320, 768), count: 0
bucket 6: resolution (384, 640), count: 48
bucket 7: resolution (448, 576), count: 60
bucket 8: resolution (512, 512), count: 12
bucket 9: resolution (576, 448), count: 0
bucket 10: resolution (640, 384), count: 0
bucket 11: resolution (704, 320), count: 0
bucket 12: resolution (768, 320), count: 0
bucket 13: resolution (832, 256), count: 0
bucket 14: resolution (896, 256), count: 0
bucket 15: resolution (960, 256), count: 0
bucket 16: resolution (1024, 256), count: 0
mean ar error (without repeats): 0.05012662418859895
prepare accelerator
Using accelerator 0.15.0 or above.
Traceback (most recent call last):
  File "A:\LoraTraining\sd-scripts\train_network.py", line 465, in <module>
    train(args)
  File "A:\LoraTraining\sd-scripts\train_network.py", line 83, in train
    text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype)
  File "A:\LoraTraining\sd-scripts\library\train_util.py", line 1306, in load_target_model
    load_stable_diffusion_format = os.path.isfile(args.pretrained_model_name_or_path)           # determine SD or Diffusers
  File "C:\Users\Anon\AppData\Local\Programs\Python\Python310\lib\genericpath.py", line 30, in isfile
    st = os.stat(path)
TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType
Traceback (most recent call last):
  File "C:\Users\Anon\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\Anon\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "A:\LoraTraining\sd-scripts\venv\Scripts\accelerate.exe\__main__.py", line 7, in <module>
  File "A:\LoraTraining\sd-scripts\venv\lib\site-packages\accelerate\commands\accelerate_cli.py", line 45, in main
    args.func(args)
  File "A:\LoraTraining\sd-scripts\venv\lib\site-packages\accelerate\commands\launch.py", line 1104, in launch_command
    simple_launcher(args)
  File "A:\LoraTraining\sd-scripts\venv\lib\site-packages\accelerate\commands\launch.py", line 567, in simple_launcher
    raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['A:\\LoraTraining\\sd-scripts\\venv\\Scripts\\python.exe', 'train_network.py', '--network_module=networks.lora', '--train_data_dir=A:\\LoraTraining\\sd-scripts\\training_data\\img', '--reg_data_dir=A:\\LoraTraining\\sd-scripts\\training_data\\reg', '--output_dir=A:\\LoraTraining\\sd-scripts\\training_data\\outputs', '--output_name= --pretrained_model_name_or_path=A:\\LoraTraining\\novelai.ckpt --vae=A:\\LoraTraining', '--max_train_epochs=10', '--train_batch_size=1', '--resolution=512', '--save_every_n_epochs=1', '--save_last_n_epochs=999', '--clip_skip=2', '--learning_rate=0.0001', '--lr_scheduler=cosine_with_restarts', '--lr_warmup_steps=0', '--network_dim=128', '--seed=1613203403', '--shuffle_caption', '--keep_tokens=0', '--max_data_loader_n_workers=8', '--mixed_precision=fp16', '--save_precision=fp16', '--caption_extension=.txt', '--prior_loss_weight=1', '--enable_bucket', '--min_bucket_reso=256', '--max_bucket_reso=1024', '--use_8bit_adam', '--xformers', '--save_model_as=safetensors', '--cache_latents']' returned non-zero exit status 1.