[Bug]: Lora not loading due to 'ValueError' for SD 1.5 based Lora's

[ReneKroon]

Is there an existing issue for this?

• [X] I have searched the existing issues and checked the recent builds/commits

What happened?

Rendering is done without the Lora, as it fails to load. Note that the code seems to have had issues in this section in the past, they are not directly related to this issue i think. Ie. #9478

Possibly related to #13319

Steps to reproduce the problem

1. Use a SD 1.5 model or derived
2. Use lora_pti ( https://github.com/cloneofsimo/lora ) to train a LORA
3. move to SD Lora folder, start program and see it's there, click configure ..
4. Run image prompt and see that it throws a ValueError while loading the Lora

What should have happened?

Lora should have been used

Sysinfo

{ "Platform": "Windows-10-10.0.22621-SP0", "Python": "3.10.6", "Version": "v1.6.0", "Commit": "5ef669de080814067961f28357256e8fe27544f4", "Script path": "C:\Users\dmesg\diffusion\automatic1111\webui", "Data path": "C:\Users\dmesg\diffusion\automatic1111\webui", "Extensions dir": "C:\Users\dmesg\diffusion\automatic1111\webui\extensions", "Checksum": "37a367562b15f3933f64fd56e60b5f00a685cd40914747b012c3112444df27f0", "Commandline": [ "launch.py", "--xformers" ], "Torch env info": { "torch_version": "2.0.1+cu118", "is_debug_build": "False", "cuda_compiled_version": "11.8", "gcc_version": null, "clang_version": null, "cmake_version": null, "os": "Microsoft Windows 11 Home", "libc_version": "N/A", "python_version": "3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)] (64-bit runtime)", "python_platform": "Windows-10-10.0.22621-SP0", "is_cuda_available": "True", "cuda_runtime_version": null, "cuda_module_loading": "LAZY", "nvidia_driver_version": "537.42", "nvidia_gpu_models": "GPU 0: NVIDIA GeForce RTX 3070 Laptop GPU", "cudnn_version": null, "pip_version": "pip3", "pip_packages": [ "numpy==1.23.5", "open-clip-torch==2.20.0", "pytorch-lightning==1.9.4", "torch==2.0.1+cu118", "torchdiffeq==0.2.3", "torchmetrics==1.1.2", "torchsde==0.2.5", "torchvision==0.15.2+cu118" ], "conda_packages": null, "hip_compiled_version": "N/A", "hip_runtime_version": "N/A", "miopen_runtime_version": "N/A", "caching_allocator_config": "", "is_xnnpack_available": "True", "cpu_info": [ "'wmic' is not recognized as an internal or external command,", "operable program or batch file." ] }, "Exceptions": [ { "exception": "not enough values to unpack (expected 2, got 1)", "traceback": [ [ "C:\Users\dmesg\diffusion\automatic1111\webui\extensions-builtin\Lora\networks.py, line 239, load_networks", "net = load_network(name, network_on_disk)" ], [ "C:\Users\dmesg\diffusion\automatic1111\webui\extensions-builtin\Lora\networks.py, line 155, load_network", "key_network_without_network_parts, network_part = key_network.split(\".\", 1)" ] ] } ], "CPU": { "model": "AMD64 Family 25 Model 68 Stepping 1, AuthenticAMD", "count logical": 16, "count physical": 8 }, "RAM": { "total": "15GB", "used": "9GB", "free": "7GB" }, "Extensions": [ { "name": "sd-webui-controlnet", "path": "C:\Users\dmesg\diffusion\automatic1111\webui\extensions\sd-webui-controlnet", "version": "e67e0177", "branch": "main", "remote": "https://github.com/Mikubill/sd-webui-controlnet.git" } ], "Inactive extensions": [], "Environment": { "COMMANDLINE_ARGS": "--xformers", "GRADIO_ANALYTICS_ENABLED": "False" }, "Config": { "samples_save": true, "samples_format": "png", "samples_filename_pattern": "", "save_images_add_number": true, "grid_save": true, "grid_format": "png", "grid_extended_filename": false, "grid_only_if_multiple": true, "grid_prevent_empty_spots": false, "grid_zip_filename_pattern": "", "n_rows": -1, "font": "", "grid_text_active_color": "#000000", "grid_text_inactive_color": "#999999", "grid_background_color": "#ffffff", "enable_pnginfo": true, "save_txt": false, "save_images_before_face_restoration": false, "save_images_before_highres_fix": false, "save_images_before_color_correction": false, "save_mask": false, "save_mask_composite": false, "jpeg_quality": 80, "webp_lossless": false, "export_for_4chan": true, "img_downscale_threshold": 4.0, "target_side_length": 4000, "img_max_size_mp": 200, "use_original_name_batch": true, "use_upscaler_name_as_suffix": false, "save_selected_only": true, "save_init_img": false, "temp_dir": "", "clean_temp_dir_at_start": false, "save_incomplete_images": false, "outdir_samples": "", "outdir_txt2img_samples": "outputs/txt2img-images", "outdir_img2img_samples": "outputs/img2img-images", "outdir_extras_samples": "outputs/extras-images", "outdir_grids": "", "outdir_txt2img_grids": "outputs/txt2img-grids", "outdir_img2img_grids": "outputs/img2img-grids", "outdir_save": "log/images", "outdir_init_images": "outputs/init-images", "save_to_dirs": true, "grid_save_to_dirs": true, "use_save_to_dirs_for_ui": false, "directories_filename_pattern": "[date]", "directories_max_prompt_words": 8, "ESRGAN_tile": 192, "ESRGAN_tile_overlap": 8, "realesrgan_enabled_models": [ "R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B" ], "upscaler_for_img2img": null, "face_restoration": false, "face_restoration_model": "CodeFormer", "code_former_weight": 0.5, "face_restoration_unload": false, "auto_launch_browser": "Local", "show_warnings": false, "show_gradio_deprecation_warnings": true, "memmon_poll_rate": 8, "samples_log_stdout": false, "multiple_tqdm": true, "print_hypernet_extra": false, "list_hidden_files": true, "disable_mmap_load_safetensors": false, "hide_ldm_prints": true, "api_enable_requests": true, "api_forbid_local_requests": true, "api_useragent": "", "unload_models_when_training": false, "pin_memory": false, "save_optimizer_state": false, "save_training_settings_to_txt": true, 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Latent space representation is what stable diffusion is working on during sampling\n(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished.\nFor img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling.", "sd_vae_checkpoint_cache": 0, "sd_vae": "Automatic", "sd_vae_overrides_per_model_preferences": true, "auto_vae_precision": true, "sd_vae_encode_method": "Full", "sd_vae_decode_method": "Full", "inpainting_mask_weight": 1.0, "initial_noise_multiplier": 1.0, "img2img_extra_noise": 0.0, "img2img_color_correction": false, "img2img_fix_steps": false, "img2img_background_color": "#ffffff", "img2img_editor_height": 720, "img2img_sketch_default_brush_color": "#ffffff", "img2img_inpaint_mask_brush_color": "#ffffff", "img2img_inpaint_sketch_default_brush_color": "#ffffff", "return_mask": false, "return_mask_composite": false, "cross_attention_optimization": "Automatic", "s_min_uncond": 0.0, "token_merging_ratio": 0.0, "token_merging_ratio_img2img": 0.0, "token_merging_ratio_hr": 0.0, 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0.5678725242614746, "gradio launch": 0.45923924446105957, "add APIs": 0.007631540298461914, "app_started_callback/api.py": 0.002000570297241211, "app_started_callback/lora_script.py": 0.0, "app_started_callback": 0.002000570297241211 } }, "Packages": [ "absl-py==2.0.0", "accelerate==0.21.0", "addict==2.4.0", "aenum==3.1.15", "aiofiles==23.2.1", "aiohttp==3.8.5", "aiosignal==1.3.1", "altair==5.1.1", "antlr4-python3-runtime==4.9.3", "anyio==3.7.1", "async-timeout==4.0.3", "attrs==23.1.0", "basicsr==1.4.2", "beautifulsoup4==4.12.2", "blendmodes==2022", "boltons==23.0.0", "cachetools==5.3.1", "certifi==2023.7.22", "cffi==1.15.1", "charset-normalizer==3.2.0", "clean-fid==0.1.35", "click==8.1.7", "clip==1.0", "colorama==0.4.6", "contourpy==1.1.1", "cssselect2==0.7.0", "cycler==0.11.0", "deprecation==2.1.0", "einops==0.4.1", "exceptiongroup==1.1.3", "facexlib==0.3.0", "fastapi==0.94.0", "ffmpy==0.3.1", "filelock==3.12.4", "filterpy==1.4.5", "flatbuffers==23.5.26", "fonttools==4.42.1", "frozenlist==1.4.0", "fsspec==2023.9.1", "ftfy==6.1.1", "future==0.18.3", "fvcore==0.1.5.post20221221", "gdown==4.7.1", "gfpgan==1.3.8", "gitdb==4.0.10", "gitpython==3.1.32", "google-auth-oauthlib==1.0.0", "google-auth==2.23.0", "gradio-client==0.5.0", "gradio==3.41.2", "grpcio==1.58.0", "h11==0.12.0", "httpcore==0.15.0", "httpx==0.24.1", "huggingface-hub==0.17.2", "idna==3.4", "imageio==2.31.3", "importlib-metadata==6.8.0", "importlib-resources==6.0.1", "inflection==0.5.1", "iopath==0.1.9", "jinja2==3.1.2", "jsonmerge==1.8.0", "jsonschema-specifications==2023.7.1", "jsonschema==4.19.0", "kiwisolver==1.4.5", "kornia==0.6.7", "lark==1.1.2", "lazy-loader==0.3", "lightning-utilities==0.9.0", "llvmlite==0.40.1", "lmdb==1.4.1", "lpips==0.1.4", "lxml==4.9.3", "markdown==3.4.4", "markupsafe==2.1.3", "matplotlib==3.8.0", "mediapipe==0.10.5", "mpmath==1.3.0", "multidict==6.0.4", "networkx==3.1", "numba==0.57.1", "numpy==1.23.5", "oauthlib==3.2.2", "omegaconf==2.2.3", "open-clip-torch==2.20.0", 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"sympy==1.12", "tabulate==0.9.0", "tb-nightly==2.15.0a20230920", "tensorboard-data-server==0.7.1", "termcolor==2.3.0", "tifffile==2023.9.18", "timm==0.9.2", "tinycss2==1.2.1", "tokenizers==0.13.3", "tomesd==0.1.3", "tomli==2.0.1", "toolz==0.12.0", "torch==2.0.1+cu118", "torchdiffeq==0.2.3", "torchmetrics==1.1.2", "torchsde==0.2.5", "torchvision==0.15.2+cu118", "tqdm==4.66.1", "trampoline==0.1.2", "transformers==4.30.2", "typing-extensions==4.8.0", "tzdata==2023.3", "urllib3==1.26.16", "uvicorn==0.23.2", "wcwidth==0.2.6", "webencodings==0.5.1", "websockets==11.0.3", "werkzeug==2.3.7", "wheel==0.41.2", "xformers==0.0.20", "yacs==0.1.8", "yapf==0.40.1", "yarl==1.9.2", "zipp==3.17.0" ] }

What browsers do you use to access the UI ?

Google Chrome

Console logs

Model loaded in 4.5s (load weights from disk: 0.8s, create model: 0.8s, apply weights to model: 0.9s, load textual inversion embeddings: 1.0s, calculate empty prompt: 0.8s).
loading network C:\Users\dmesg\diffusion\automatic1111\webui\models\Lora\final_lora.safetensors: ValueError
Traceback (most recent call last):
  File "C:\Users\dmesg\diffusion\automatic1111\webui\extensions-builtin\Lora\networks.py", line 239, in load_networks
    net = load_network(name, network_on_disk)
  File "C:\Users\dmesg\diffusion\automatic1111\webui\extensions-builtin\Lora\networks.py", line 155, in load_network
    key_network_without_network_parts, network_part = key_network.split(".", 1)
ValueError: not enough values to unpack (expected 2, got 1)

100%|██████████████████████████████████████████████████████████████████████████████████| 20/20 [00:02<00:00,  8.02it/s]

Additional information

No response

[neerhow]

same problem here

[storywriter]

I have same problem, and I solve this problem with below way:

# /stable-diffusion-webui/extensions-builtin/Lora/networks.py
# L: 154

# Before
        key_network_without_network_parts, network_part = key_network.split(".", 1)

# Ater
        if "." in key_network:
            key_network_without_network_parts, network_part = key_network.split(".", 1)
        else:
            key_network_without_network_parts = key_network
            network_part = None

The variable key_network gets values like below. There are some values have no dot ., because those values are top level properties. if key_network gets top level properties, it substitute into the variable key_network_without_network_parts.

Sample values key_network gets:

key_network: 'alphas_cumprod'
key_network: 'alphas_cumprod_prev'
key_network: 'betas'
key_network: 'cond_stage_model.transformer.text_model.embeddings.position_embedding.weight'
key_network: 'cond_stage_model.transformer.text_model.embeddings.position_ids'
key_network: 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight'
key_network: 'cond_stage_model.transformer.text_model.encoder.layers.0.layer_norm1.bias'
key_network: 'cond_stage_model.transformer.text_model.encoder.layers.0.layer_norm1.weight'
key_network: 'cond_stage_model.transformer.text_model.encoder.layers.0.layer_norm2.bias'
key_network: 'cond_stage_model.transformer.text_model.encoder.layers.0.layer_norm2.weight'
key_network: 'cond_stage_model.transformer.text_model.encoder.layers.0.mlp.fc1.bias'
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