problem training lore - Githubissues

there is a problem, i don't know where exactly when i try to train lora i try different models and it still doesn't work. ill be glad if someone will find the problem.
`13:58:18-783361 INFO     accelerate launch --num_cpu_threads_per_process=2 "./train_network.py" --enable_bucket
                         --min_bucket_reso=256 --max_bucket_reso=2048
                         --pretrained_model_name_or_path="C:/Users/j/Documents/a1111/stable-diffusion-webui/models/S
                         table-diffusion/realisticVisionV60B1_v60B1VAE.safetensors"
                         --train_data_dir="C:\Users\j\Documents\a1111\lora traning data\test\image"
                         --resolution="768,768" --output_dir="C:\Users\j\Documents\a1111\lora traning
                         data\test\model" --logging_dir="C:\Users\j\Documents\a1111\lora traning data\test\log"
                         --network_alpha="1" --save_model_as=safetensors --network_module=networks.lora
                         --text_encoder_lr=5e-05 --unet_lr=0.0001 --network_dim=8 --output_name="last"
                         --lr_scheduler_num_cycles="1" --no_half_vae --learning_rate="0.0001" --lr_scheduler="cosine"
                         --lr_warmup_steps="140" --train_batch_size="2" --max_train_steps="1400"
                         --save_every_n_epochs="1" --mixed_precision="fp16" --save_precision="fp16" --cache_latents
                         --optimizer_type="AdamW8bit" --max_grad_norm="1" --max_data_loader_n_workers="0"
                         --bucket_reso_steps=64 --xformers --bucket_no_upscale --noise_offset=0.0
prepare tokenizer
Using DreamBooth method.
prepare images.
found directory C:\Users\j\Documents\a1111\lora traning data\test\image\100_test contains 28 image files
No caption file found for 28 images. Training will continue without captions for these images. If class token exists, it will be used. / 28枚の画像にキャプションファイルが見つかりませんでした。これらの画像についてはキャプションなしで学習を 続行します。class tokenが存在する場合はそれを使います。
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\357899421_822294102667661_2397216796649422802_n.jpg
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\358045145_1087556515553872_7328103429567946199_n.jpg
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\358053195_780436100540601_4810672643826577373_n.jpg
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\358961137_152298244537935_690518984658140002_n.jpg
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\359555336_1303571573857210_4374378250726296964_n.jpg
C:\Users\j\Documents\a1111\lora traning data\test\image\100_test\363510473_3509950062656315_7905028743974878263_n.jpg... and 23 more
2800 train images with repeating.
0 reg images.
no regularization images / 正則化画像が見つかりませんでした
[Dataset 0]
  batch_size: 2
  resolution: (768, 768)
  enable_bucket: True
  min_bucket_reso: 256
  max_bucket_reso: 2048
  bucket_reso_steps: 64
  bucket_no_upscale: True

  [Subset 0 of Dataset 0]
    image_dir: "C:\Users\j\Documents\a1111\lora traning data\test\image\100_test"
    image_count: 28
    num_repeats: 100
    shuffle_caption: False
    keep_tokens: 0
    caption_dropout_rate: 0.0
    caption_dropout_every_n_epoches: 0
    caption_tag_dropout_rate: 0.0
    caption_prefix: None
    caption_suffix: None
    color_aug: False
    flip_aug: False
    face_crop_aug_range: None
    random_crop: False
    token_warmup_min: 1,
    token_warmup_step: 0,
    is_reg: False
    class_tokens: test
    caption_extension: .caption

[Dataset 0]
loading image sizes.
100%|████████████████████████████████████████████████████████████████████████████████| 28/28 [00:00<00:00, 2410.87it/s]
make buckets
min_bucket_reso and max_bucket_reso are ignored if bucket_no_upscale is set, because bucket reso is defined by image size automatically / bucket_no_upscaleが指定された場合は、bucketの解像度は画像サイズから自動計算されるため、min_bucket_resoとmax_bucket_resoは無視されます
number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）
bucket 0: resolution (128, 128), count: 100
bucket 1: resolution (192, 192), count: 200
bucket 2: resolution (192, 256), count: 200
bucket 3: resolution (256, 256), count: 100
bucket 4: resolution (320, 320), count: 100
bucket 5: resolution (384, 384), count: 100
bucket 6: resolution (448, 448), count: 100
bucket 7: resolution (640, 768), count: 500
bucket 8: resolution (640, 832), count: 800
bucket 9: resolution (704, 768), count: 400
bucket 10: resolution (768, 768), count: 100
bucket 11: resolution (832, 640), count: 100
mean ar error (without repeats): 0.03822719710816732
preparing accelerator
loading model for process 0/1
load StableDiffusion checkpoint: C:/Users/j/Documents/a1111/stable-diffusion-webui/models/Stable-diffusion/realisticVisionV60B1_v60B1VAE.safetensors
UNet2DConditionModel: 64, 8, 768, False, False
loading u-net: <All keys matched successfully>
loading vae: <All keys matched successfully>
loading text encoder: <All keys matched successfully>
Enable xformers for U-Net
A matching Triton is not available, some optimizations will not be enabled.
Error caught was: No module named 'triton'
import network module: networks.lora
[Dataset 0]
caching latents.
checking cache validity...
100%|██████████████████████████████████████████████████████████████████████████████████████████| 28/28 [00:00<?, ?it/s]
caching latents...
100%|██████████████████████████████████████████████████████████████████████████████████| 28/28 [00:05<00:00,  5.00it/s]
create LoRA network. base dim (rank): 8, alpha: 1.0
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder:
create LoRA for Text Encoder: 72 modules.
create LoRA for U-Net: 192 modules.
enable LoRA for text encoder
enable LoRA for U-Net
prepare optimizer, data loader etc.
Traceback (most recent call last):
  File "C:\Users\j\Documents\a1111\kohya_ss\library\train_util.py", line 3444, in get_optimizer
    import bitsandbytes as bnb
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\__init__.py", line 6, in <module>
    from . import cuda_setup, utils, research
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\research\__init__.py", line 1, in <module>
    from . import nn
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\research\nn\__init__.py", line 1, in <module>
    from .modules import LinearFP8Mixed, LinearFP8Global
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\research\nn\modules.py", line 8, in <module>
    from bitsandbytes.optim import GlobalOptimManager
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\optim\__init__.py", line 6, in <module>
    from bitsandbytes.cextension import COMPILED_WITH_CUDA
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\cextension.py", line 5, in <module>
    from .cuda_setup.main import evaluate_cuda_setup
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\bitsandbytes\cuda_setup\main.py", line 21, in <module>
    from .paths import determine_cuda_runtime_lib_path
ModuleNotFoundError: No module named 'bitsandbytes.cuda_setup.paths'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\j\Documents\a1111\kohya_ss\train_network.py", line 1012, in <module>
    trainer.train(args)
  File "C:\Users\j\Documents\a1111\kohya_ss\train_network.py", line 342, in train
    optimizer_name, optimizer_args, optimizer = train_util.get_optimizer(args, trainable_params)
  File "C:\Users\j\Documents\a1111\kohya_ss\library\train_util.py", line 3446, in get_optimizer
    raise ImportError("No bitsandbytes / bitsandbytesがインストールされていないようです")
ImportError: No bitsandbytes / bitsandbytesがインストールされていないようです
Traceback (most recent call last):
  File "C:\Users\ja\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\j\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\Scripts\accelerate.exe\__main__.py", line 7, in <module>
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\accelerate\commands\accelerate_cli.py", line 47, in main
    args.func(args)
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 986, in launch_command
    simple_launcher(args)
  File "C:\Users\j\Documents\a1111\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 628, in simple_launcher
    raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['C:\\Users\\j\\Documents\\a1111\\kohya_ss\\venv\\Scripts\\python.exe', './train_network.py', '--enable_bucket', '--min_bucket_reso=256', '--max_bucket_reso=2048', '--pretrained_model_name_or_path=C:/Users/j/Documents/a1111/stable-diffusion-webui/models/Stable-diffusion/realisticVisionV60B1_v60B1VAE.safetensors', '--train_data_dir=C:\\Users\\j\\Documents\\a1111\\lora traning data\\test\\image', '--resolution=768,768', '--output_dir=C:\\Users\\j\\Documents\\a1111\\lora traning data\\test\\model', '--logging_dir=C:\\Users\\j\\Documents\\a1111\\lora traning data\\test\\log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-05', '--unet_lr=0.0001', '--network_dim=8', '--output_name=last', '--lr_scheduler_num_cycles=1', '--no_half_vae', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=140', '--train_batch_size=2', '--max_train_steps=1400', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--cache_latents', '--optimizer_type=AdamW8bit', '--max_grad_norm=1', '--max_data_loader_n_workers=0', '--bucket_reso_steps=64', '--xformers', '--bucket_no_upscale', '--noise_offset=0.0']' returned non-zero exit status 1.`
thanks.
bmaltais / kohya_ss

problem training lore #1795
