chrbratt
commented
1 year ago Same problem here. Latest update from repository. Any ide is welcome? :)
You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
Replace CrossAttention.forward to use xformers
caching latents.
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import network module: networks.lora
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.
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CUDA SETUP: Loading binary D:\kohya_ss\venv\lib\site-packages\bitsandbytes\libbitsandbytes_cuda116.dll...
use 8-bit Adam optimizer
running training / 学習開始
num train images * repeats / 学習画像の数×繰り返し回数: 7200
num reg images / 正則化画像の数: 0
num batches per epoch / 1epochのバッチ数: 3600
num epochs / epoch数: 1
batch size per device / バッチサイズ: 2
total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ（並列学習、勾配合計含む）: 2
gradient accumulation steps / 勾配を合計するステップ数 = 1
total optimization steps / 学習ステップ数: 3150
Traceback (most recent call last):
File "D:\kohya_ss\train_network.py", line 573, in <module>
train(args)
File "D:\kohya_ss\train_network.py", line 356, in train
"ss_noise_offset": args.noise_offset,
AttributeError: 'Namespace' object has no attribute 'noise_offset'
Traceback (most recent call last):
File "C:\Users\bratt\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\bratt\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in _run_code
exec(code, run_globals)
File "D:\kohya_ss\venv\Scripts\accelerate.exe\__main__.py", line 7, in <module>
File "D:\kohya_ss\venv\lib\site-packages\accelerate\commands\accelerate_cli.py", line 45, in main
args.func(args)
File "D:\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 1104, in launch_command
simple_launcher(args)
File "D:\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 567, in simple_launcher
raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['D:\\StableDiffusion\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5', '--train_data_dir=D:\\StableDiffusion\\LoraTraining Data\\cbratt\\image', '--resolution=512,512', '--output_dir=D:\\StableDiffusion\\LoraTraining Data\\cbratt', '--logging_dir=D:\\StableDiffusion\\LoraTraining Data\\cbratt', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--output_name=cbratt2', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=315', '--train_batch_size=2', '--max_train_steps=3150', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--cache_latents', '--bucket_reso_steps=64', '--gradient_checkpointing', '--xformers', '--use_8bit_adam', '--bucket_no_upscale']' returned non-zero exit status 1.
Crimsonfart
kohya-ss
HWESTA00
yvonnechen888
Swizzler121
Trahloc
Hi All,
Any one knows how to fix this error? Or where can I skip this 'noise_offset' option?
running training / 学習開始 num train images * repeats / 学習画像の数×繰り返し回数: 1000 num reg images / 正則化画像の数: 0 num batches per epoch / 1epochのバッチ数: 1000 num epochs / epoch数: 1 batch size per device / バッチサイズ: 1 total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ（並列学習、勾配合計含む）: 1 gradient accumulation steps / 勾配を合計するステップ数 = 1 total optimization steps / 学習ステップ数: 1000 Traceback (most recent call last): File "C:\Users\Kohya\kohya_ss\train_network.py", line 573, in <module> train(args) File "C:\Users\Kohya\kohya_ss\train_network.py", line 356, in train "ss_noise_offset": args.noise_offset, AttributeError: 'Namespace' object has no attribute 'noise_offset' Traceback (most recent call last): File "C:\Users\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\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in _run_code exec(code, run_globals) File "C:\Users\Documents\Kohya\kohya_ss\venv\Scripts\accelerate.exe\__main__.py", line 7, in <module> File "C:\Users\Documents\Kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\accelerate_cli.py", line 45, in main args.func(args) File "C:\Users\Documents\Kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 1104, in launch_command simple_launcher(args) File "C:\Users\Documents\Kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 567, in simple_launcher raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd) subprocess.CalledProcessError: Command '['C:\\Users\\Documents\\Kohya\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=E:/stable-diffusion-webui/models/Stable-diffusion/anything-v3-full.safetensors', '--train_data_dir=C:/Users/Documents/Kohya/Lora/Character/image', '--resolution=512,512', '--output_dir=C:/Users/Documents/Kohya/Lora/Character/model', '--logging_dir=C:/Users/Documents/Kohya/Lora/Character/log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--output_name=testman', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=100', '--train_batch_size=1', '--max_train_steps=1000', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--cache_latents', '--bucket_reso_steps=64', '--xformers', '--use_8bit_adam', '--bucket_no_upscale']' returned non-zero exit status 1.