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SDXL Lora training failing even with square images dataset/captions: RuntimeError: Error(s) in loading state_dict for UNet2DConditionModel: Missing key(s) in state_dict: #1367

Open gloomiebloomie opened 4 weeks ago

gloomiebloomie commented 4 weeks ago

I installed kohya-ss with ease but have had a hard time creating the dataset to get training start on sdxl model. I'm triying to use the dreamturbo model as well as base sdxl model for this with no luck. I have 58 1024x0124 images and the captions are just tags given by tagger in kohya-ss. I've tried the beginner as well as advanced lora training as well. I am on windows 10 executed from powershell with admin privileges. I've tried adam8 optimizer first with no luck so it is lion here I can change that back though. My dataset is in data/train/3_zkz/(images.jpg/png).

Here are my config details: pretrained_model_name_or_path = "C:/Users/socie/Documents/newui/new_ComfyUI_windows_portable_nvidia_cu121_or_cpu/ComfyUI_windows_portable/ComfyUI/models/checkpoints/sd_xl_base_1.0.safetensors" train_data_dir = "C:/Users/socie/Downloads/data/train" resolution = "1024,1024" enable_bucket = true min_bucket_reso = 256 max_bucket_reso = 1024 output_name = "aki" output_dir = "./output" save_model_as = "safetensors" save_every_n_epochs = 2 max_train_epochs = 10 train_batch_size = 1 network_train_unet_only = false network_train_text_encoder_only = false learning_rate = 0.0001 unet_lr = 0.0001 text_encoder_lr = 0.00001 lr_scheduler = "cosine_with_restarts" optimizer_type = "Lion" lr_scheduler_num_cycles = 1 network_module = "networks.lora" network_dim = 8 network_alpha = 32 logging_dir = "./logs" caption_extension = ".txt" shuffle_caption = true keep_tokens = 0 max_token_length = 255 seed = 1337 prior_loss_weight = 1 clip_skip = 2 mixed_precision = "fp16" save_precision = "fp16" xformers = true cache_latents = true persistent_data_loader_workers = true lr_warmup_steps = 0 no_half_vae = true

Here is the error I got:

16:55:53-891443 INFO Training started with config file / 训练开始，使用配置文件: C:\users\socie\Downloads\lora-scripts\config\autosave\20240610-165553.toml 16:55:53-894442 INFO Task 12c7214c-d92d-46a4-85f0-1c18877aa2c9 created 2024-06-10 16:56:01 INFO Loading settings from train_util.py:3744 C:\users\socie\Downloads\lora-scripts\config\autosave\20240610-165553.to ml... INFO C:\users\socie\Downloads\lora-scripts\config\autosave\20240610-165553 train_util.py:3763 2024-06-10 16:56:01 INFO prepare tokenizer train_util.py:4227 INFO update token length: 255 train_util.py:4244 INFO Using DreamBooth method. train_network.py:172 INFO prepare images. train_util.py:1572 INFO found directory C:\Users\socie\Downloads\data\train\3_zkz contains 58 train_util.py:1519 image files INFO 174 train images with repeating. train_util.py:1613 INFO 0 reg images. train_util.py:1616 WARNING no regularization images / 正則化画像が見つかりませんでした train_util.py:1621 INFO [Dataset 0] config_util.py:565 batch_size: 1 resolution: (1024, 1024) enable_bucket: True network_multiplier: 1.0 min_bucket_reso: 256 max_bucket_reso: 1024 bucket_reso_steps: 64 bucket_no_upscale: False

                           [Subset 0 of Dataset 0]
                             image_dir: "C:\Users\socie\Downloads\data\train\3_zkz"
                             image_count: 58
                             num_repeats: 3
                             shuffle_caption: True
                             keep_tokens: 0
                             keep_tokens_separator:
                             secondary_separator: None
                             enable_wildcard: False
                             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: zkz
                             caption_extension: .txt

                INFO     [Dataset 0]                                                              config_util.py:571
                INFO     loading image sizes.                                                      train_util.py:853

100%|████████████████████████████████████████████████████████████████████████████████| 58/58 [00:00<00:00, 9664.29it/s] INFO make buckets train_util.py:859 INFO number of images (including repeats) / train_util.py:905 各bucketの画像枚数（繰り返し回数を含む） INFO bucket 0: resolution (1024, 1024), count: 174 train_util.py:910 INFO mean ar error (without repeats): 0.0 train_util.py:915 INFO preparing accelerator train_network.py:225 accelerator device: cuda INFO loading model for process 0/1 train_util.py:4385 INFO load StableDiffusion checkpoint: train_util.py:4341 C:/Users/socie/Documents/newui/new_ComfyUI_windows_portable_nvidia_cu121 _or_cpu/ComfyUI_windows_portable/ComfyUI/models/checkpoints/sd_xl_base_1 .0.safetensors INFO UNet2DConditionModel: 64, 8, 768, False, False original_unet.py:1387 Traceback (most recent call last): File "C:\users\socie\Downloads\lora-scripts\sd-scripts\train_network.py", line 1117, in trainer.train(args) File "C:\users\socie\Downloads\lora-scripts\sd-scripts\train_network.py", line 234, in train model_version, text_encoder, vae, unet = self.load_target_model(args, weight_dtype, accelerator) File "C:\users\socie\Downloads\lora-scripts\sd-scripts\train_network.py", line 101, in load_target_model textencoder, vae, unet, = train_util.load_target_model(args, weight_dtype, accelerator) File "C:\users\socie\Downloads\lora-scripts\sd-scripts\library\train_util.py", line 4387, in load_target_model text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model( File "C:\users\socie\Downloads\lora-scripts\sd-scripts\library\train_util.py", line 4342, in _load_target_model text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint( File "C:\users\socie\Downloads\lora-scripts\sd-scripts\library\model_util.py", line 1008, in load_models_from_stable_diffusion_checkpoint info = unet.load_state_dict(converted_unet_checkpoint) File "C:\users\socie\Downloads\lora-scripts\venv\lib\site-packages\torch\nn\modules\module.py", line 2153, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for UNet2DConditionModel: Missing key(s) in state_dict: "down_blocks.0.attentions.0.norm.weight", "down_blocks.0.attentions.0.norm.bias", "down_blocks.0.attentions.0.proj_in.weight", "down_blocks.0.attentions.0.proj_in.bias", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_q.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_k.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_v.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_out.0.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_out.0.bias", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.0.proj.weight", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.0.proj.bias", 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"up_blocks.3.attentions.2.transformer_blocks.0.norm2.bias", "up_blocks.3.attentions.2.transformer_blocks.0.norm3.weight", "up_blocks.3.attentions.2.transformer_blocks.0.norm3.bias", "up_blocks.3.attentions.2.proj_out.weight", "up_blocks.3.attentions.2.proj_out.bias", "up_blocks.3.resnets.0.norm1.weight", "up_blocks.3.resnets.0.norm1.bias", "up_blocks.3.resnets.0.conv1.weight", "up_blocks.3.resnets.0.conv1.bias", "up_blocks.3.resnets.0.time_emb_proj.weight", "up_blocks.3.resnets.0.time_emb_proj.bias", "up_blocks.3.resnets.0.norm2.weight", "up_blocks.3.resnets.0.norm2.bias", "up_blocks.3.resnets.0.conv2.weight", "up_blocks.3.resnets.0.conv2.bias", "up_blocks.3.resnets.0.conv_shortcut.weight", "up_blocks.3.resnets.0.conv_shortcut.bias", "up_blocks.3.resnets.1.norm1.weight", "up_blocks.3.resnets.1.norm1.bias", "up_blocks.3.resnets.1.conv1.weight", "up_blocks.3.resnets.1.conv1.bias", "up_blocks.3.resnets.1.time_emb_proj.weight", "up_blocks.3.resnets.1.time_emb_proj.bias", "up_blocks.3.resnets.1.norm2.weight", "up_blocks.3.resnets.1.norm2.bias", "up_blocks.3.resnets.1.conv2.weight", "up_blocks.3.resnets.1.conv2.bias", "up_blocks.3.resnets.1.conv_shortcut.weight", "up_blocks.3.resnets.1.conv_shortcut.bias", "up_blocks.3.resnets.2.norm1.weight", "up_blocks.3.resnets.2.norm1.bias", "up_blocks.3.resnets.2.conv1.weight", "up_blocks.3.resnets.2.conv1.bias", "up_blocks.3.resnets.2.time_emb_proj.weight", "up_blocks.3.resnets.2.time_emb_proj.bias", "up_blocks.3.resnets.2.norm2.weight", "up_blocks.3.resnets.2.norm2.bias", "up_blocks.3.resnets.2.conv2.weight", "up_blocks.3.resnets.2.conv2.bias", "up_blocks.3.resnets.2.conv_shortcut.weight", "up_blocks.3.resnets.2.conv_shortcut.bias". Unexpected key(s) in state_dict: "down_blocks.1.attentions.0.transformer_blocks.1.attn1.to_k.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn1.to_out.0.bias", "down_blocks.1.attentions.0.transformer_blocks.1.attn1.to_out.0.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn1.to_q.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn1.to_v.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn2.to_k.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn2.to_out.0.bias", "down_blocks.1.attentions.0.transformer_blocks.1.attn2.to_out.0.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn2.to_q.weight", "down_blocks.1.attentions.0.transformer_blocks.1.attn2.to_v.weight", "down_blocks.1.attentions.0.transformer_blocks.1.ff.net.0.proj.bias", "down_blocks.1.attentions.0.transformer_blocks.1.ff.net.0.proj.weight", "down_blocks.1.attentions.0.transformer_blocks.1.ff.net.2.bias", "down_blocks.1.attentions.0.transformer_blocks.1.ff.net.2.weight", "down_blocks.1.attentions.0.transformer_blocks.1.norm1.bias", "down_blocks.1.attentions.0.transformer_blocks.1.norm1.weight", "down_blocks.1.attentions.0.transformer_blocks.1.norm2.bias", "down_blocks.1.attentions.0.transformer_blocks.1.norm2.weight 16:56:06-165346 ERROR Training failed / 训练失败

rockerBOO commented 4 weeks ago

loading SDXL into the non-SDXL trainer so make sure it's using the SDXL version (sdxl_train_network.py)