Error saving to to Safetensor format: "ERROR is You are trying to save a non contiguous tensor: model.diffusion_model.input_blocks.0.0.weight which is not allowed. It either means you are trying to save tensors which are reference of each other in which case it's recommended to save only the full tensors, and reslice at load time, or simply call .contiguous() on your tensor to pack it before saving.
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full error log needed to track easily
I guess, the metadata exported by model-mixer is not good enough.
Thank you for your feed back so quickly! |
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Did the following to produce the log below: First did 2 saves to LoRA at fp16, fp32, and then using CPU - none showed up in A111 but all worked fine when I changed the setting to show all LoRA files regardless. So perhaps this is just an A1111 or metadata issue unrelated to the Safetensor error I'm seeing saving full models. I used the app "Beyond Compare" to pull up the hex beginning of the first test file I exported and also recent merged model I extracted to LoRA using the Kohya script to compare headers. Not exact at all, but perhaps it'll give you some info. Could send generated files also if those would be better: Header of LoRA extraction that shows up in A1111: Export from dev branch to LoRA: And here is the full log from my session. After saving those 3 LoRA exports I tried to save the model to Safetensor and got the usual error I see listed in the title: venv "D:\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.11 (tags/v3.10.11:7d4cc5a, Apr 5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)]
Version: v1.6.0-295-g9c1c0da0
Commit hash: 9c1c0da026cb7ef091a0f3fa24b14ae8634f6de5
Launching Web UI with arguments: --opt-sdp-attention --no-half-vae --opt-channelslast --skip-torch-cuda-test --skip-version-check --ckpt-dir e:\Stable Diffusion Checkpoints
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
[-] ADetailer initialized. version: 23.11.0, num models: 9
2023-11-07 20:58:10,746 - ControlNet - INFO - ControlNet v1.1.416
ControlNet preprocessor location: D:\stable-diffusion-webui\extensions\3sd-webui-controlnet\annotator\downloads
2023-11-07 20:58:10,801 - ControlNet - INFO - ControlNet v1.1.416
Tag Autocomplete: Could not locate model-keyword extension, Lora trigger word completion will be limited to those added through the extra networks menu.
Loading weights [31e35c80fc] from e:\Stable Diffusion Checkpoints\SDXL\sd_xl_base_1.0.safetensors
Creating model from config: D:\stable-diffusion-webui\repositories\generative-models\configs\inference\sd_xl_base.yaml
Loading VAE weights specified in settings: D:\stable-diffusion-webui\models\VAE\sdxl_vae.safetensors
Applying attention optimization: sdp... done.
Model loaded in 4.2s (load weights from disk: 0.5s, create model: 0.2s, apply weights to model: 2.1s, apply channels_last: 0.6s, calculate empty prompt: 0.6s).
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
Startup time: 9.5s (prepare environment: 0.5s, import torch: 1.4s, import gradio: 0.4s, setup paths: 0.3s, initialize shared: 0.2s, other imports: 0.3s, load scripts: 1.4s, create ui: 4.6s, gradio launch: 0.3s).
debugs = ['elemental merge']
use_extra_elements = True
config hash = e4295162844f50a5c37a3d2bc78d365731e293143c0c27178470ebc8bd7cea3f
- mm_use [True, False, False, False, False]
- model_a SDXL\2023-11-06 - TreyAnastasio - TE1 1e7 - TE2 1e5 - b2 - 15img-20rep-mix1300-step00001500.safetensors [1a7f166bf5]
- base_model SDXL\sd_xl_base_1.0.safetensors [31e35c80fc]
- max_models 5
- models ['SDXL\\2023-11-07 - TreyAnastasio - 15img - 40rep - 500reg Yushan-step00002100.safetensors [97c56e48e2]']
- modes ['Sum']
- calcmodes ['Normal']
- usembws [[]]
- weights ['0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5']
- alpha [0.5]
- adjust
- use elemental [False]
- elementals ['']
- Parse elemental merge...
model_a = SDXL_2023-11-06 - TreyAnastasio - TE1 1e7 - TE2 1e5 - b2 - 15img-20rep-mix1300-step00001500
Loading from file e:\Stable Diffusion Checkpoints\SDXL\2023-11-06 - TreyAnastasio - TE1 1e7 - TE2 1e5 - b2 - 15img-20rep-mix1300-step00001500.safetensors...
isxl = True
compact_mode = False
Loading model SDXL_2023-11-07 - TreyAnastasio - 15img - 40rep - 500reg Yushan-step00002100...
Loading from file e:\Stable Diffusion Checkpoints\SDXL\2023-11-07 - TreyAnastasio - 15img - 40rep - 500reg Yushan-step00002100.safetensors...
mode = Sum, alpha = 0.5
Stage #1/2: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2515/2515 [00:08<00:00, 295.59it/s]
Check uninitialized #2/2: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2515/2515 [00:00<00:00, 628758.10it/s]
Save unchanged weights #2/2: 0it [00:00, ?it/s]
Creating model from config: D:\stable-diffusion-webui\repositories\generative-models\configs\inference\sd_xl_base.yaml
Loading VAE weights specified in settings: cached sdxl_vae.safetensors
Applying attention optimization: sdp... done.
Model loaded in 1.6s (create model: 0.2s, apply weights to model: 1.1s).
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:05<00:00, 5.98it/s]
Total progress: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:06<00:00, 5.09it/s]
- load original base model SDXL\sd_xl_base_1.0.safetensors [31e35c80fc]...█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:06<00:00, 6.14it/s]
- get the merged model...
- loading script.patches...
- base lora_patch
Applying attention optimization: sdp... done.
check difference: 0%| | 0/2515 [00:00<?, ?it/s]
- svd calc device = cuda
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
create LoRA network. base dim (rank): 64, alpha: 64
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
create LoRA network. base dim (rank): 64, alpha: 64
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
Text encoder is different. 0.0009765625 > 1e-06
calculating by svd
Calculating svd: lora_unet_output_blocks_5_1_proj_out: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 986/986 [01:12<00:00, 13.65it/s]
create LoRA network from weights
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
enable LoRA for text encoder
enable LoRA for U-Net
Loading extracted LoRA weights: <All keys matched successfully>
Extracted LoRA saved in D:\stable-diffusion-webui\models\Lora\Test-Export-To-Lora.safetensors
- load original base model SDXL\sd_xl_base_1.0.safetensors [31e35c80fc]...
- get the merged model...
- base lora_patch
Applying attention optimization: sdp... done.
check difference: 0%| | 0/2515 [00:00<?, ?it/s]
- svd calc device = cuda
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
create LoRA network. base dim (rank): 64, alpha: 64
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
create LoRA network. base dim (rank): 64, alpha: 64
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
Text encoder is different. 0.0009765625 > 1e-06
calculating by svd
Calculating svd: lora_unet_output_blocks_5_1_proj_out: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 986/986 [01:11<00:00, 13.82it/s]
create LoRA network from weights
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
enable LoRA for text encoder
enable LoRA for U-Net
Loading extracted LoRA weights: <All keys matched successfully>
Extracted LoRA saved in D:\stable-diffusion-webui\models\Lora\Test-Export-To-Lora-f32.safetensors
- load original base model SDXL\sd_xl_base_1.0.safetensors [31e35c80fc]...
- get the merged model...
- base lora_patch
Applying attention optimization: sdp... done.
check difference: 0%| | 0/2515 [00:00<?, ?it/s]
- svd calc device = cpu
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
loading original SDXL model
building U-Net
loading U-Net from checkpoint
U-Net: <All keys matched successfully>
building text encoders
loading text encoders from checkpoint
text encoder 1: <All keys matched successfully>
text encoder 2: <All keys matched successfully>
building VAE
loading VAE from checkpoint
VAE: <All keys matched successfully>
create LoRA network. base dim (rank): 4, alpha: 4
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
create LoRA network. base dim (rank): 4, alpha: 4
neuron dropout: p=None, rank dropout: p=None, module dropout: p=None
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
Text encoder is different. 0.0009765625 > 1e-06
calculating by svd
Calculating svd: lora_unet_output_blocks_5_1_proj_out: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 986/986 [04:20<00:00, 3.78it/s]
create LoRA network from weights
create LoRA for Text Encoder 1:
create LoRA for Text Encoder 2:
create LoRA for Text Encoder: 264 modules.
create LoRA for U-Net: 722 modules.
enable LoRA for text encoder
enable LoRA for U-Net
Loading extracted LoRA weights: <All keys matched successfully>
Extracted LoRA saved in D:\stable-diffusion-webui\models\Lora\Test-Export-To-Lora-f4-cpu.safetensors
Load state_dict from shared.sd_model..
- base lora_patch
Applying attention optimization: sdp... done.
Saving...
isxl = True
ERROR: Couldn't saved:D:\stable-diffusion-webui\models\Stable-diffusion\Test-Full-Model-Safetensors-Save-Prune-FP16-No.VAE.safetensors,ERROR is You are trying to save a non contiguous tensor: `model.diffusion_model.input_blocks.0.0.weight` which is not allowed. It either means you are trying to save tensors which are reference of each other in which case it's recommended to save only the full tensors, and reslice at load time, or simply call `.contiguous()` on your tensor to pack it before saving.
System Info / Config: {
"Platform": "Windows-10-10.0.19045-SP0",
"Python": "3.10.11",
"Version": "v1.6.0-295-g9c1c0da0",
"Commit": "9c1c0da026cb7ef091a0f3fa24b14ae8634f6de5",
"Script path": "D:\\stable-diffusion-webui",
"Data path": "D:\\stable-diffusion-webui",
"Extensions dir": "D:\\stable-diffusion-webui\\extensions",
"Checksum": "7d63153c45021d1d401a0ff26b77ba9ae7eb1a5c4f3c5faf7808f06ed0fa2074",
"Commandline": [
"launch.py",
"--opt-sdp-attention",
"--no-half-vae",
"--opt-channelslast",
"--skip-torch-cuda-test",
"--skip-version-check",
"--ckpt-dir",
"e:\\Stable Diffusion Checkpoints"
],
"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": "version 3.28.0-rc2",
"os": "Microsoft Windows 10 Pro",
"libc_version": "N/A",
"python_version": "3.10.11 (tags/v3.10.11:7d4cc5a, Apr 5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)] (64-bit runtime)",
"python_platform": "Windows-10-10.0.19045-SP0",
"is_cuda_available": "True",
"cuda_runtime_version": "11.8.89\r",
"cuda_module_loading": "LAZY",
"nvidia_driver_version": "531.68",
"nvidia_gpu_models": "GPU 0: NVIDIA GeForce RTX 4090",
"cudnn_version": "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v11.8\\bin\\cudnn_ops_train64_8.dll",
"pip_version": "pip3",
"pip_packages": [
"groundingdino==0.1.0+torch2.0.1.cu118",
"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==1.2.0",
"torchsde==0.2.6",
"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": [
"Architecture=9",
"CurrentClockSpeed=3000",
"DeviceID=CPU0",
"Family=207",
"L2CacheSize=16384",
"L2CacheSpeed=",
"Manufacturer=GenuineIntel",
"MaxClockSpeed=3000",
"Name=13th Gen Intel(R) Core(TM) i9-13900K",
"ProcessorType=3",
"Revision="
]
},
"Exceptions": [],
"CPU": {
"model": "Intel64 Family 6 Model 183 Stepping 1, GenuineIntel",
"count logical": 32,
"count physical": 24
},
"RAM": {
"total": "64GB",
"used": "19GB",
"free": "45GB"
},
"Extensions": [
{
"name": "1-sd-dynamic-prompts",
"path": "D:\\stable-diffusion-webui\\extensions\\1-sd-dynamic-prompts",
"version": "e07ff1d7",
"branch": "main",
"remote": "https://github.com/adieyal/sd-dynamic-prompts.git"
},
{
"name": "2adetailer",
"path": "D:\\stable-diffusion-webui\\extensions\\2adetailer",
"version": "6b41b3db",
"branch": "main",
"remote": "https://github.com/Bing-su/adetailer.git"
},
{
"name": "3sd-webui-controlnet",
"path": "D:\\stable-diffusion-webui\\extensions\\3sd-webui-controlnet",
"version": "05ef0b1c",
"branch": "main",
"remote": "https://github.com/Mikubill/sd-webui-controlnet.git"
},
{
"name": "b1111-sd-webui-tagcomplete",
"path": "D:\\stable-diffusion-webui\\extensions\\b1111-sd-webui-tagcomplete",
"version": "58804796",
"branch": "main",
"remote": "https://github.com/DominikDoom/a1111-sd-webui-tagcomplete.git"
},
{
"name": "csd-webui-cads",
"path": "D:\\stable-diffusion-webui\\extensions\\csd-webui-cads",
"version": "1dba7e18",
"branch": "main",
"remote": "https://github.com/v0xie/sd-webui-cads.git"
},
{
"name": "dsd-webui-model-mixer",
"path": "D:\\stable-diffusion-webui\\extensions\\dsd-webui-model-mixer",
"version": "38d7429e",
"branch": "save-merge-loras",
"remote": "https://github.com/wkpark/sd-webui-model-mixer.git"
},
{
"name": "sd-Img2img-batch-interrogator",
"path": "D:\\stable-diffusion-webui\\extensions\\sd-Img2img-batch-interrogator",
"version": "7f4e4eb0",
"branch": "main",
"remote": "https://github.com/Alvi-alvarez/sd-Img2img-batch-interrogator.git"
},
{
"name": "sd-extension-system-info",
"path": "D:\\stable-diffusion-webui\\extensions\\sd-extension-system-info",
"version": "1841cf76",
"branch": "main",
"remote": "https://github.com/vladmandic/sd-extension-system-info.git"
},
{
"name": "sd-webui-aspect-ratio-helper",
"path": "D:\\stable-diffusion-webui\\extensions\\sd-webui-aspect-ratio-helper",
"version": "99fcf9b0",
"branch": "main",
"remote": "https://github.com/thomasasfk/sd-webui-aspect-ratio-helper.git"
},
{
"name": "sd-webui-cleaner",
"path": "D:\\stable-diffusion-webui\\extensions\\sd-webui-cleaner",
"version": "d89d173a",
"branch": "main",
"remote": "https://github.com/novitalabs/sd-webui-cleaner.git"
},
{
"name": "sd-webui-supermerger",
"path": "D:\\stable-diffusion-webui\\extensions\\sd-webui-supermerger",
"version": "64a6064e",
"branch": "main",
"remote": "https://github.com/hako-mikan/sd-webui-supermerger.git"
},
{
"name": "stable-diffusion-webui-model-toolkit",
"path": "D:\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-model-toolkit",
"version": "cf824587",
"branch": "master",
"remote": "https://github.com/arenasys/stable-diffusion-webui-model-toolkit.git"
}
],
"Inactive extensions": [],
"Environment": {
"COMMANDLINE_ARGS": "--opt-sdp-attention --no-half-vae --opt-channelslast --skip-torch-cuda-test --skip-version-check --ckpt-dir \"e:\\Stable Diffusion Checkpoints\"",
"GRADIO_ANALYTICS_ENABLED": "False"
},
"Config": {
"samples_save": true,
"samples_format": "png",
"samples_filename_pattern": "[prompt_spaces]",
"save_images_add_number": true,
"grid_save": false,
"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": "d:\\temp",
"clean_temp_dir_at_start": true,
"save_incomplete_images": false,
"outdir_samples": "E:\\Stable Diffusion Images",
"outdir_txt2img_samples": "E:\\Stable Diffusion Images",
"outdir_img2img_samples": "E:\\Stable Diffusion Images",
"outdir_extras_samples": "E:\\Stable Diffusion Images",
"outdir_grids": "E:\\Stable Diffusion Images",
"outdir_txt2img_grids": "E:\\Stable Diffusion Images",
"outdir_img2img_grids": "E:\\Stable Diffusion Images",
"outdir_save": "E:\\Stable Diffusion Images",
"outdir_init_images": "E:\\Stable Diffusion Images",
"save_to_dirs": true,
"grid_save_to_dirs": false,
"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": false,
"memmon_poll_rate": 8,
"samples_log_stdout": false,
"multiple_tqdm": true,
"print_hypernet_extra": false,
"list_hidden_files": true,
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"gdown==4.7.1",
"gfpgan==1.3.8",
"gitdb==4.0.11",
"gitpython==3.1.32",
"google-auth-oauthlib==1.1.0",
"google-auth==2.23.3",
"gradio-client==0.5.0",
"gradio==3.41.2",
"groundingdino==0.1.0+torch2.0.1.cu118",
"grpcio==1.59.0",
"h11==0.12.0",
"httpcore==0.15.0",
"httpx==0.24.1",
"huggingface-hub==0.18.0",
"idna==3.4",
"imageio-ffmpeg==0.4.9",
"imageio==2.31.6",
"importlib-metadata==6.8.0",
"importlib-resources==6.1.0",
"inflection==0.5.1",
"iopath==0.1.9",
"jinja2==3.1.2",
"jmespath==0.10.0",
"joblib==1.3.2",
"jsonmerge==1.8.0",
"jsonschema-specifications==2023.7.1",
"jsonschema==4.19.1",
"kiwisolver==1.4.5",
"kornia==0.6.7",
"lark==1.1.2",
"lazy-loader==0.3",
"lightning-utilities==0.9.0",
"litelama==0.1.7",
"llvmlite==0.41.1",
"lmdb==1.4.1",
"lpips==0.1.4",
"lxml==4.9.3",
"markdown-it-py==3.0.0",
"markdown==3.5",
"markupsafe==2.1.3",
"matplotlib==3.8.0",
"mdurl==0.1.2",
"mediapipe==0.10.7",
"mmcv==2.0.1",
"mmdet==3.2.0",
"mmengine==0.9.1",
"mmyolo==0.6.0",
"model-index==0.1.11",
"moviepy==0.2.3.2",
"mpmath==1.3.0",
"multidict==6.0.4",
"networkx==3.2",
"numba==0.58.1",
"numpy==1.23.5",
"oauthlib==3.2.2",
"omegaconf==2.2.3",
"open-clip-torch==2.20.0",
"opencv-contrib-python==4.8.1.78",
"opencv-python==4.8.1.78",
"opendatalab==0.0.10",
"openmim==0.3.9",
"openxlab==0.0.28",
"ordered-set==4.1.0",
"orjson==3.9.9",
"oss2==2.17.0",
"packaging==23.2",
"pandas==2.1.1",
"piexif==1.1.3",
"pillow==9.5.0",
"pip==23.3.1",
"platformdirs==3.11.0",
"portalocker==2.8.2",
"prettytable==3.9.0",
"protobuf==3.20.0",
"psutil==5.9.5",
"py-cpuinfo==9.0.0",
"pyaescrypt==6.1.0",
"pyasn1-modules==0.3.0",
"pyasn1==0.5.0",
"pycocotools==2.0.7",
"pycparser==2.21",
"pycryptodome==3.19.0",
"pydantic-core==2.10.1",
"pydantic==1.10.13",
"pydub==0.25.1",
"pygments==2.16.1",
"pyparsing==3.1.1",
"pysocks==1.7.1",
"python-dateutil==2.8.2",
"python-multipart==0.0.6",
"pytorch-lightning==1.9.4",
"pytz==2023.3.post1",
"pywavelets==1.4.1",
"pywin32==306",
"pyyaml==6.0.1",
"realesrgan==0.3.0",
"referencing==0.30.2",
"regex==2023.10.3",
"reportlab==4.0.6",
"requests-oauthlib==1.3.1",
"requests==2.28.2",
"resize-right==0.0.2",
"rich==13.4.2",
"rpds-py==0.10.6",
"rsa==4.9",
"safetensors==0.3.1",
"scenedetect==0.6.2",
"scikit-image==0.21.0",
"scikit-learn==1.3.2",
"scipy==1.11.3",
"seaborn==0.13.0",
"segment-anything-hq==0.3",
"segment-anything==1.0",
"semantic-version==2.10.0",
"send2trash==1.8.2",
"sentencepiece==0.1.99",
"setuptools==60.2.0",
"shapely==2.0.2",
"shellingham==1.5.4",
"six==1.16.0",
"smmap==5.0.1",
"sniffio==1.3.0",
"sounddevice==0.4.6",
"soupsieve==2.5",
"starlette==0.26.1",
"supervision==0.6.0",
"svglib==1.5.1",
"sympy==1.12",
"tabulate==0.9.0",
"tb-nightly==2.16.0a20231025",
"tensorboard-data-server==0.7.2",
"termcolor==2.3.0",
"terminaltables==3.1.10",
"thop==0.1.1.post2209072238",
"threadpoolctl==3.2.0",
"tifffile==2023.9.26",
"timm==0.9.2",
"tinycss2==1.2.1",
"tokenizers==0.13.3",
"tomesd==0.1.3",
"tomli==2.0.1",
"tomlkit==0.12.0",
"toolz==0.12.0",
"torch==2.0.1+cu118",
"torchdiffeq==0.2.3",
"torchmetrics==1.2.0",
"torchsde==0.2.6",
"torchvision==0.15.2+cu118",
"tqdm==4.65.2",
"trampoline==0.1.2",
"transformers==4.30.2",
"typer==0.9.0",
"typing-extensions==4.8.0",
"tzdata==2023.3",
"ultralytics==8.0.201",
"urllib3==1.26.18",
"uvicorn==0.23.2",
"wcwidth==0.2.8",
"webencodings==0.5.1",
"websockets==11.0.3",
"werkzeug==3.0.1",
"yacs==0.1.8",
"yapf==0.40.2",
"yarl==1.9.2",
"zipp==3.17.0"
]
} |
|
Amazing! Thank you!! Will have a chance to check later - Super helpful functionality for my workflow. |
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TL;DR: Been getting error saving models out to Safetensors format for a while - always worked around saving to CKPT. Testing new LoRA export realized I will need safetensor functionality working to use that upcoming feature.
Hello again!
I get the following error whenever I try to save out a merge to .safetensors format:
"ERROR is You are trying to save a non contiguous tensor:
model.diffusion_model.input_blocks.0.0.weightwhich is not allowed. It either means you are trying to save tensors which are reference of each other in which case it's recommended to save only the full tensors, and reslice at load time, or simply call.contiguous()on your tensor to pack it before saving."I've been getting this error for a little while, but I've just untoggled the safetensors option and saved to ckpt instead and that's worked without issue. Howver, I pulled the development branch w/ early LoRA export functionality and I realized this above error might cause issues when exporting to LoRA.
My first attempts exporting to Lora and Lycoris worked great! But - for some reason the exported LoRAs don't show up in A1111 unless I turn off this option in settings, "Always show all networks on the Lora page (otherwise, those detected as for incompatible version of Stable Diffusion will be hidden)"
So I'm thinking A1111s not recognizing the Model Mixer generated LoRAs as valid for SDXL - My guess is that it's related to the safetensor error I get when trying to save full models out to Safetensors. I don't have a workaround that would work in this case.
Really sorry if this is user error (Re: something in my A111 settings), but I do get it on both the current 1.6 version and the latest development version v1.6.0-295-g9c1c0da0 which has the tweaks Automatic added recently related to the other issue in this forum.
Thanks so much for everything - love the extension!
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