Repository: stable-diffusion-webui
Issue: [Bug]:  RuntimeError: mixed dtype (CPU): expect parameter to have scalar type of Float
Labels: asking-for-help-with-local-system-issues

### Is there an existing issue for this?

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

### What happened?

Everytime i am enabling Controlnet and using openpose to test a pose i am getting this error "RuntimeError: mixed dtype (CPU): expect parameter to have scalar type of Float" .. without controlnet image is generating..

CMD Args i am using :
set COMMANDLINE_ARGS=--medvram --xformers --no-half-vae --upcast-sampling --precision full --skip-torch-cuda-test --update-check



### Steps to reproduce the problem

1. Start A1111 and write a prompt
2. Enable controlnet and load the openpose model or any other without preprocessor
3. run it and will see the error ( tried many times disabling othe extensions and restarting SD did not work )


### What should have happened?

Should have generated the image in the pose provided in the openpose.

### Sysinfo

{
    "Platform": "Windows-10-10.0.22621-SP0",
    "Python": "3.10.6",
    "Version": "v1.6.0-2-g4afaaf8a",
    "Commit": "4afaaf8a020c1df457bcf7250cb1c7f609699fa7",
    "Script path": "D:\\AI\\stable-diffusion\\stable-diffusion-webui\\stable-diffusion-webui",
    "Data path": "D:\\AI\\stable-diffusion\\stable-diffusion-webui\\stable-diffusion-webui",
    "Extensions dir": "D:\\AI\\stable-diffusion\\stable-diffusion-webui\\stable-diffusion-webui\\extensions",
    "Checksum": "5a96617ad514da27b53b562a63b2734e8e429f1a8c6942944adad0900a5a698a",
    "Commandline": [
        "launch.py",
        "--medvram",
        "--xformers",
        "--no-half-vae",
        "--upcast-sampling",
        "--precision",
        "full",
        "--skip-torch-cuda-test",
        "--update-check",
        "--dump-sysinfo"
    ],
    "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 Single Language",
        "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": "546.17",
        "nvidia_gpu_models": "GPU 0: NVIDIA GeForce GTX 1650",
        "cudnn_version": null,
        "pip_version": "pip3",
        "pip_packages": [
            "mypy-extensions==1.0.0",
            "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==0.11.4",
            "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": [
            "Architecture=9",
            "CurrentClockSpeed=3000",
            "DeviceID=CPU0",
            "Family=107",
            "L2CacheSize=3072",
            "L2CacheSpeed=",
            "Manufacturer=AuthenticAMD",
            "MaxClockSpeed=3000",
            "Name=AMD Ryzen 5 4600H with Radeon Graphics         ",
            "ProcessorType=3",
            "Revision=24577"
        ]
    },
    "Exceptions": [],
    "CPU": {
        "model": "AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD",
        "count logical": 12,
        "count physical": 6
    },
    "RAM": {
        "total": "7GB",
        "used": "4GB",
        "free": "3GB"
    },
    "Extensions": [],
    "Inactive extensions": [],
    "Environment": {
        "COMMANDLINE_ARGS": "--medvram --xformers --no-half-vae --upcast-sampling --precision full --skip-torch-cuda-test --update-check --dump-sysinfo",
        "GRADIO_ANALYTICS_ENABLED": "False"
    },
    "Config": "'NoneType' object has no attribute 'data'",
    "Startup": null,
    "Packages": [
        "absl-py==1.4.0",
        "accelerate==0.21.0",
        "addict==2.4.0",
        "aenum==3.1.14",
        "aiofiles==23.1.0",
        "aiohttp==3.8.4",
        "aiosignal==1.3.1",
        "albumentations==1.3.1",
        "altair==5.0.1",
        "antlr4-python3-runtime==4.9.3",
        "anyio==3.7.0",
        "async-timeout==4.0.2",
        "attrs==23.1.0",
        "av==10.0.0",
        "basicsr==1.4.2",
        "beautifulsoup4==4.12.2",
        "bidict==0.22.1",
        "blendmodes==2022",
        "boltons==23.0.0",
        "cachetools==5.3.1",
        "certifi==2023.5.7",
        "cffi==1.15.1",
        "chardet==5.2.0",
        "charset-normalizer==3.1.0",
        "clean-fid==0.1.35",
        "click==8.1.3",
        "clip==1.0",
        "colorama==0.4.6",
        "coloredlogs==15.0.1",
        "contourpy==1.1.0",
        "cssselect2==0.7.0",
        "cycler==0.11.0",
        "cython==0.29.35",
        "dataclasses-json==0.5.14",
        "datasets==2.13.1",
        "deprecation==2.1.0",
        "diffusers==0.17.1",
        "dill==0.3.6",
        "easydict==1.10",
        "einops==0.4.1",
        "exceptiongroup==1.1.1",
        "facexlib==0.3.0",
        "fairscale==0.4.13",
        "fake-useragent==1.4.0",
        "fastapi==0.94.0",
        "ffmpy==0.3.0",
        "filelock==3.12.2",
        "filterpy==1.4.5",
        "flatbuffers==23.5.26",
        "fonttools==4.40.0",
        "frozenlist==1.3.3",
        "fsspec==2023.6.0",
        "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==2.20.0",
        "gpt-index==0.4.24",
        "gradio-client==0.5.0",
        "gradio==3.41.2",
        "greenlet==3.0.0",
        "grpcio==1.56.0",
        "h11==0.12.0",
        "httpcore==0.15.0",
        "httpx==0.24.1",
        "huggingface-hub==0.15.1",
        "humanfriendly==10.0",
        "idna==3.4",
        "ifnude==0.0.3",
        "image-reward==1.4",
        "imageio-ffmpeg==0.4.9",
        "imageio==2.31.1",
        "importlib-metadata==6.7.0",
        "importlib-resources==6.0.1",
        "inflection==0.5.1",
        "insightface==0.7.3",
        "iopath==0.1.9",
        "jinja2==3.1.2",
        "joblib==1.2.0",
        "jsonmerge==1.8.0",
        "jsonpatch==1.33",
        "jsonpointer==2.4",
        "jsonschema==4.17.3",
        "kiwisolver==1.4.4",
        "kornia==0.6.7",
        "langchain==0.0.132",
        "langsmith==0.0.49",
        "lark==1.1.2",
        "lazy-loader==0.2",
        "lightning-utilities==0.8.0",
        "linkify-it-py==2.0.2",
        "llvmlite==0.40.1",
        "lmdb==1.4.1",
        "lpips==0.1.4",
        "lxml==4.9.2",
        "markdown-it-py==2.2.0",
        "markdown==3.4.3",
        "markupsafe==2.1.3",
        "marshmallow==3.20.1",
        "matplotlib==3.7.1",
        "mdit-py-plugins==0.3.3",
        "mdurl==0.1.2",
        "mediapipe==0.10.1",
        "mpmath==1.3.0",
        "multidict==6.0.4",
        "multiprocess==0.70.14",
        "mypy-extensions==1.0.0",
        "networkx==3.1",
        "numba==0.57.1",
        "numexpr==2.8.7",
        "numpy==1.23.5",
        "oauthlib==3.2.2",
        "omegaconf==2.2.3",
        "onnx==1.14.0",
        "onnxruntime==1.15.0",
        "open-clip-torch==2.20.0",
        "openai==0.28.1",
        "opencv-contrib-python==4.7.0.72",
        "opencv-python-headless==4.7.0.72",
        "opencv-python==4.8.0.76",
        "orjson==3.9.1",
        "packaging==23.1",
        "pandas==2.0.2",
        "piexif==1.1.3",
        "pillow==9.5.0",
        "pims==0.6.0",
        "pip==23.1.2",
        "platformdirs==3.8.0",
        "portalocker==2.7.0",
        "prettytable==3.8.0",
        "protobuf==3.20.3",
        "psutil==5.9.5",
        "py-cpuinfo==9.0.0",
        "pyarrow==12.0.1",
        "pyasn1-modules==0.3.0",
        "pyasn1==0.5.0",
        "pycparser==2.21",
        "pydantic==1.10.9",
        "pydub==0.25.1",
        "pygments==2.15.1",
        "pyparsing==3.1.0",
        "pyreadline3==3.4.1",
        "pyrsistent==0.19.3",
        "pysocks==1.7.1",
        "python-dateutil==2.8.2",
        "python-engineio==4.8.0",
        "python-multipart==0.0.6",
        "python-socketio==5.7.2",
        "pytorch-lightning==1.9.4",
        "pytz==2023.3",
        "pywavelets==1.4.1",
        "pywin32==306",
        "pyyaml==6.0",
        "qudida==0.0.4",
        "realesrgan==0.3.0",
        "regex==2023.6.3",
        "reportlab==4.0.4",
        "requests-oauthlib==1.3.1",
        "requests==2.31.0",
        "resize-right==0.0.2",
        "rich==13.4.2",
        "rsa==4.9",
        "safetensors==0.3.1",
        "scikit-image==0.21.0",
        "scikit-learn==1.2.2",
        "scipy==1.10.1",
        "seaborn==0.12.2",
        "semantic-version==2.10.0",
        "send2trash==1.8.2",
        "sentencepiece==0.1.99",
        "setuptools==63.2.0",
        "simple-websocket==1.0.0",
        "six==1.16.0",
        "slicerator==1.1.0",
        "smmap==5.0.0",
        "sniffio==1.3.0",
        "sounddevice==0.4.6",
        "soupsieve==2.4.1",
        "sqlalchemy==1.4.49",
        "starlette==0.26.1",
        "svglib==1.5.1",
        "sympy==1.12",
        "tabulate==0.9.0",
        "tb-nightly==2.14.0a20230624",
        "tenacity==8.2.3",
        "tensorboard-data-server==0.7.1",
        "termcolor==2.3.0",
        "threadpoolctl==3.1.0",
        "tifffile==2023.4.12",
        "tiktoken==0.5.1",
        "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==0.11.4",
        "torchsde==0.2.5",
        "torchvision==0.15.2+cu118",
        "tqdm==4.64.0",
        "trampoline==0.1.2",
        "transformers==4.30.2",
        "typing-extensions==4.6.3",
        "typing-inspect==0.9.0",
        "tzdata==2023.3",
        "uc-micro-py==1.0.2",
        "ultralytics==8.0.122",
        "urllib3==2.0.6",
        "uvicorn==0.22.0",
        "wcwidth==0.2.6",
        "webencodings==0.5.1",
        "websocket-client==1.6.4",
        "websockets==11.0.3",
        "werkzeug==2.3.6",
        "wheel==0.40.0",
        "wsproto==1.2.0",
        "xformers==0.0.20",
        "xxhash==3.2.0",
        "yacs==0.1.8",
        "yapf==0.40.1",
        "yarl==1.9.2",
        "zipp==3.15.0",
        "zipunicode==1.1.1"
    ]
}

### What browsers do you use to access the UI ?

_No response_

### Console logs

```Shell
venv "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: v1.6.0-2-g4afaaf8a
Commit hash: 4afaaf8a020c1df457bcf7250cb1c7f609699fa7
You are up to date with the most recent release.
Launching Web UI with arguments: --medvram --xformers --no-half-vae --upcast-sampling --precision full --skip-torch-cuda-test --update-check
Tag Autocomplete: Could not locate model-keyword extension, Lora trigger word completion will be limited to those added through the extra networks menu.
[-] ADetailer initialized. version: 23.7.6, num models: 12
CivitAI Browser+: Aria2 RPC started
2023-11-27 19:10:20,487 - ControlNet - INFO - ControlNet v1.1.419
ControlNet preprocessor location: D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\downloads
2023-11-27 19:10:21,047 - ControlNet - INFO - ControlNet v1.1.419
Loading weights [15012c538f] from D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\models\Stable-diffusion\realisticVisionV51_v51VAE.safetensors
Creating model from config: D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\configs\v1-inference.yaml
D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\gradio_extensons.py:25: GradioUnusedKwargWarning: You have unused kwarg parameters in Slider, please remove them: {'max_width': 100}
  res = original_IOComponent_init(self, *args, **kwargs)
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 96.1s (prepare environment: 7.1s, import torch: 36.4s, import gradio: 12.4s, setup paths: 8.6s, initialize shared: 1.0s, other imports: 8.0s, setup codeformer: 1.5s, setup gfpgan: 0.4s, list SD models: 0.2s, load scripts: 11.6s, initialize extra networks: 0.8s, create ui: 6.3s, gradio launch: 2.0s, add APIs: 0.3s).
Loading VAE weights specified in settings: D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\models\VAE\vae-ft-mse-840000-ema-pruned.safetensors
Applying attention optimization: xformers... done.
Model loaded in 151.6s (load weights from disk: 4.1s, create model: 1.2s, apply weights to model: 130.7s, apply half(): 0.2s, apply dtype to VAE: 0.1s, load VAE: 9.8s, load textual inversion embeddings: 1.2s, calculate empty prompt: 4.1s).
  0%|                                                                                           | 0/20 [00:29<?, ?it/s]
*** Error completing request
*** Arguments: ('task(kgn73suglrqm625)', 'a girl sitting under a treee', '', [], 20, 'Euler a', 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x00000228E5690DF0>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, False, {'ad_model': 'face_yolov8n.pt', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, False, 'MultiDiffusion', False, True, 1024, 1024, 96, 96, 48, 4, 'None', 2, False, 10, 1, 1, 64, False, False, False, False, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, True, 960, 64, True, True, True, False, UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
    Traceback (most recent call last):
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 732, in process_images
        res = process_images_inner(p)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 867, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 1140, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 201, in forward
        devices.test_for_nans(x_out, "unet")
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\devices.py", line 136, in test_for_nans
        raise NansException(message)
    modules.devices.NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.

---
100%|██████████████████████████████████████████████████████████████████████████████████| 20/20 [02:06<00:00,  6.35s/it]
[Tiled VAE]: input_size: torch.Size([1, 4, 64, 96]), tile_size: 64, padding: 11████████| 20/20 [01:29<00:00,  4.72s/it]
[Tiled VAE]: split to 1x2 = 2 tiles. Optimal tile size 64x64, original tile size 64x64
[Tiled VAE]: Fast mode enabled, estimating group norm parameters on 64 x 42 image
[Tiled VAE]: Executing Decoder Task Queue: 100%|█████████████████████████████████████| 246/246 [00:24<00:00, 10.16it/s]
[Tiled VAE]: Done in 35.347s, max VRAM alloc 2835.561 MB
D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=None`.
  warnings.warn(msg)
Total progress: 100%|██████████████████████████████████████████████████████████████████| 20/20 [02:29<00:00,  7.49s/it]
2023-11-27 19:21:53,808 - ControlNet - WARNING - Unable to determine version for ControlNet model 'controlnet11Models_openpose [73c2b67d]'.
2023-11-27 19:21:53,809 - ControlNet - INFO - Loading model: controlnet11Models_openpose [73c2b67d]
2023-11-27 19:21:54,945 - ControlNet - INFO - Loaded state_dict from [D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\models\controlnet11Models_openpose.safetensors]
2023-11-27 19:21:54,956 - ControlNet - INFO - controlnet_default_config
2023-11-27 19:22:46,098 - ControlNet - INFO - ControlNet model controlnet11Models_openpose [73c2b67d] loaded.
2023-11-27 19:22:46,292 - ControlNet - INFO - Loading preprocessor: none
2023-11-27 19:22:46,293 - ControlNet - INFO - preprocessor resolution = -1
2023-11-27 19:22:46,763 - ControlNet - INFO - ControlNet Hooked - Time = 53.15157890319824
  0%|                                                                                           | 0/20 [00:07<?, ?it/s]
*** Error completing request
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    Traceback (most recent call last):
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 732, in process_images
        res = process_images_inner(p)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 867, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 420, in process_sample
        return process.sample_before_CN_hack(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 1140, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 169, in forward
        x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 26, in __call__
        return self.__sub_func(self.__orig_func, *args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_unet.py", line 48, in apply_model
        return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1538, in _call_impl
        result = forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 827, in forward_webui
        raise e
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 824, in forward_webui
        return forward(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\hook.py", line 561, in forward
        control = param.control_model(x=x_in, hint=hint, timesteps=timesteps, context=context, y=y)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 31, in forward
        return self.control_model(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 314, in forward
        h = module(h, emb, context)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 98, in forward
        x = layer(x, emb)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 317, in forward
        return checkpoint(
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\util.py", line 167, in checkpoint
        return func(*inputs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 329, in _forward
        h = self.in_layers(x)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\container.py", line 217, in forward
        input = module(input)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\repositories\generative-models\sgm\modules\diffusionmodules\util.py", line 275, in forward
        return super().forward(x.float()).type(x.dtype)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 459, in network_GroupNorm_forward
        return originals.GroupNorm_forward(self, input)
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\normalization.py", line 273, in forward
        return F.group_norm(
      File "D:\AI\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2530, in group_norm
        return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
    RuntimeError: mixed dtype (CPU): expect parameter to have scalar type of Float

---
```


### Additional information

_No response_