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AUTOMATIC1111 / stable-diffusion-webui

Stable Diffusion web UI
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[Bug]: Safetensors VAE won't load #10006

Open Bammargiela opened 1 year ago

Bammargiela commented 1 year ago

Is there an existing issue for this?

What happened?

I've had this problem for a while. I've tried updating, didn't work. I've tried using the quick menu and the one in setting and receiving the same error. All of the VAEs from official stable diffusion 2.x aren't working. Even the unclip ones. I've tried renaming it to the model and to the default name. I changed the name so I know which is which.

Steps to reproduce the problem

  1. Using quick menu or the drop down in settings select a VAE
  2. Wait
  3. Receive error

What should have happened?

VAE should have loaded.

Commit where the problem happens

a9fed7c3

What platforms do you use to access the UI ?

Windows, Other/Cloud

What browsers do you use to access the UI ?

Google Chrome

Command Line Arguments

in the colab I'm using:
!python launch.py --listen --xformers --enable-insecure-extension-access --theme dark --gradio-queue --clip-models-path /content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/models/CLIP --ckpt-dir /content/fused-models --lora-dir /content/fused-lora --multiple

List of extensions

a1111-sd-webui-locon batchlinks-webui deforum-for-automatic1111-webui openpose-editor posex sd-civitai-browser sd-webui-3d-open-pose-editor sd-webui-additional-networks sd-webui-aspect-ratio-helper sd-webui-controlnet sd-webui-depth-lib sd-webui-tunnels sd_webui_stealth_pnginfo stable-diffusion-webui-catppuccin stable-diffusion-webui-huggingface stable-diffusion-webui-images-browser stable-diffusion-webui-rembg stable-diffusion-webui-two-shot LDSR Lora ScuNET SwinIR prompt-bracket-checker

Console logs

Startup time: 234.0s (import gradio: 2.9s, import ldm: 7.3s, other imports: 4.6s, list extensions: 1.0s, setup codeformer: 0.3s, load scripts: 146.8s, load SD checkpoint: 48.4s, create ui: 21.3s, gradio launch: 1.4s).
Loading VAE weights specified in settings: /content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/models/VAE/21768diffusion_pytorch_model.safetensors
changing setting sd_vae to 21768diffusion_pytorch_model.safetensors: RuntimeError
Traceback (most recent call last):
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/modules/shared.py", line 568, in set
    self.data_labels[key].onchange()
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/modules/call_queue.py", line 15, in f
    res = func(*args, **kwargs)
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/webui.py", line 147, in <lambda>
    shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/modules/sd_vae.py", line 207, in reload_vae_weights
    load_vae(sd_model, vae_file, vae_source)
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/modules/sd_vae.py", line 146, in load_vae
    _load_vae_dict(model, vae_dict_1)
  File "/content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui/modules/sd_vae.py", line 171, in _load_vae_dict
    model.first_stage_model.load_state_dict(vae_dict_1)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1671, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for AutoencoderKL:
    Missing key(s) in state_dict: "encoder.down.0.block.0.norm1.weight", "encoder.down.0.block.0.norm1.bias", "encoder.down.0.block.0.conv1.weight", "encoder.down.0.block.0.conv1.bias", "encoder.down.0.block.0.norm2.weight", "encoder.down.0.block.0.norm2.bias", "encoder.down.0.block.0.conv2.weight", "encoder.down.0.block.0.conv2.bias", "encoder.down.0.block.1.norm1.weight", "encoder.down.0.block.1.norm1.bias", "encoder.down.0.block.1.conv1.weight", "encoder.down.0.block.1.conv1.bias", "encoder.down.0.block.1.norm2.weight", "encoder.down.0.block.1.norm2.bias", "encoder.down.0.block.1.conv2.weight", "encoder.down.0.block.1.conv2.bias", "encoder.down.0.downsample.conv.weight", "encoder.down.0.downsample.conv.bias", "encoder.down.1.block.0.norm1.weight", "encoder.down.1.block.0.norm1.bias", "encoder.down.1.block.0.conv1.weight", "encoder.down.1.block.0.conv1.bias", "encoder.down.1.block.0.norm2.weight", "encoder.down.1.block.0.norm2.bias", "encoder.down.1.block.0.conv2.weight", "encoder.down.1.block.0.conv2.bias", "encoder.down.1.block.0.nin_shortcut.weight", "encoder.down.1.block.0.nin_shortcut.bias", "encoder.down.1.block.1.norm1.weight", "encoder.down.1.block.1.norm1.bias", "encoder.down.1.block.1.conv1.weight", "encoder.down.1.block.1.conv1.bias", "encoder.down.1.block.1.norm2.weight", "encoder.down.1.block.1.norm2.bias", "encoder.down.1.block.1.conv2.weight", "encoder.down.1.block.1.conv2.bias", "encoder.down.1.downsample.conv.weight", "encoder.down.1.downsample.conv.bias", "encoder.down.2.block.0.norm1.weight", "encoder.down.2.block.0.norm1.bias", "encoder.down.2.block.0.conv1.weight", "encoder.down.2.block.0.conv1.bias", "encoder.down.2.block.0.norm2.weight", "encoder.down.2.block.0.norm2.bias", "encoder.down.2.block.0.conv2.weight", "encoder.down.2.block.0.conv2.bias", "encoder.down.2.block.0.nin_shortcut.weight", "encoder.down.2.block.0.nin_shortcut.bias", "encoder.down.2.block.1.norm1.weight", "encoder.down.2.block.1.norm1.bias", "encoder.down.2.block.1.conv1.weight", "encoder.down.2.block.1.conv1.bias", "encoder.down.2.block.1.norm2.weight", "encoder.down.2.block.1.norm2.bias", "encoder.down.2.block.1.conv2.weight", "encoder.down.2.block.1.conv2.bias", "encoder.down.2.downsample.conv.weight", "encoder.down.2.downsample.conv.bias", "encoder.down.3.block.0.norm1.weight", "encoder.down.3.block.0.norm1.bias", "encoder.down.3.block.0.conv1.weight", "encoder.down.3.block.0.conv1.bias", "encoder.down.3.block.0.norm2.weight", "encoder.down.3.block.0.norm2.bias", "encoder.down.3.block.0.conv2.weight", "encoder.down.3.block.0.conv2.bias", "encoder.down.3.block.1.norm1.weight", "encoder.down.3.block.1.norm1.bias", "encoder.down.3.block.1.conv1.weight", "encoder.down.3.block.1.conv1.bias", "encoder.down.3.block.1.norm2.weight", "encoder.down.3.block.1.norm2.bias", "encoder.down.3.block.1.conv2.weight", "encoder.down.3.block.1.conv2.bias", "encoder.mid.block_1.norm1.weight", "encoder.mid.block_1.norm1.bias", "encoder.mid.block_1.conv1.weight", "encoder.mid.block_1.conv1.bias", "encoder.mid.block_1.norm2.weight", "encoder.mid.block_1.norm2.bias", "encoder.mid.block_1.conv2.weight", "encoder.mid.block_1.conv2.bias", "encoder.mid.attn_1.norm.weight", "encoder.mid.attn_1.norm.bias", "encoder.mid.attn_1.q.weight", "encoder.mid.attn_1.q.bias", "encoder.mid.attn_1.k.weight", "encoder.mid.attn_1.k.bias", "encoder.mid.attn_1.v.weight", "encoder.mid.attn_1.v.bias", "encoder.mid.attn_1.proj_out.weight", "encoder.mid.attn_1.proj_out.bias", "encoder.mid.block_2.norm1.weight", "encoder.mid.block_2.norm1.bias", "encoder.mid.block_2.conv1.weight", "encoder.mid.block_2.conv1.bias", "encoder.mid.block_2.norm2.weight", "encoder.mid.block_2.norm2.bias", "encoder.mid.block_2.conv2.weight", "encoder.mid.block_2.conv2.bias", "encoder.norm_out.weight", "encoder.norm_out.bias", "decoder.mid.block_1.norm1.weight", "decoder.mid.block_1.norm1.bias", "decoder.mid.block_1.conv1.weight", "decoder.mid.block_1.conv1.bias", "decoder.mid.block_1.norm2.weight", "decoder.mid.block_1.norm2.bias", "decoder.mid.block_1.conv2.weight", "decoder.mid.block_1.conv2.bias", "decoder.mid.attn_1.norm.weight", "decoder.mid.attn_1.norm.bias", "decoder.mid.attn_1.q.weight", "decoder.mid.attn_1.q.bias", "decoder.mid.attn_1.k.weight", "decoder.mid.attn_1.k.bias", "decoder.mid.attn_1.v.weight", "decoder.mid.attn_1.v.bias", "decoder.mid.attn_1.proj_out.weight", "decoder.mid.attn_1.proj_out.bias", "decoder.mid.block_2.norm1.weight", "decoder.mid.block_2.norm1.bias", "decoder.mid.block_2.conv1.weight", "decoder.mid.block_2.conv1.bias", "decoder.mid.block_2.norm2.weight", "decoder.mid.block_2.norm2.bias", "decoder.mid.block_2.conv2.weight", "decoder.mid.block_2.conv2.bias", "decoder.up.0.block.0.norm1.weight", "decoder.up.0.block.0.norm1.bias", "decoder.up.0.block.0.conv1.weight", "decoder.up.0.block.0.conv1.bias", "decoder.up.0.block.0.norm2.weight", "decoder.up.0.block.0.norm2.bias", "decoder.up.0.block.0.conv2.weight", "decoder.up.0.block.0.conv2.bias", "decoder.up.0.block.0.nin_shortcut.weight", "decoder.up.0.block.0.nin_shortcut.bias", "decoder.up.0.block.1.norm1.weight", "decoder.up.0.block.1.norm1.bias", "decoder.up.0.block.1.conv1.weight", "decoder.up.0.block.1.conv1.bias", "decoder.up.0.block.1.norm2.weight", "decoder.up.0.block.1.norm2.bias", "decoder.up.0.block.1.conv2.weight", "decoder.up.0.block.1.conv2.bias", "decoder.up.0.block.2.norm1.weight", "decoder.up.0.block.2.norm1.bias", "decoder.up.0.block.2.conv1.weight", "decoder.up.0.block.2.conv1.bias", "decoder.up.0.block.2.norm2.weight", "decoder.up.0.block.2.norm2.bias", "decoder.up.0.block.2.conv2.weight", "decoder.up.0.block.2.conv2.bias", "decoder.up.1.block.0.norm1.weight", "decoder.up.1.block.0.norm1.bias", "decoder.up.1.block.0.conv1.weight", "decoder.up.1.block.0.conv1.bias", "decoder.up.1.block.0.norm2.weight", "decoder.up.1.block.0.norm2.bias", "decoder.up.1.block.0.conv2.weight", "decoder.up.1.block.0.conv2.bias", "decoder.up.1.block.0.nin_shortcut.weight", "decoder.up.1.block.0.nin_shortcut.bias", "decoder.up.1.block.1.norm1.weight", "decoder.up.1.block.1.norm1.bias", "decoder.up.1.block.1.conv1.weight", "decoder.up.1.block.1.conv1.bias", "decoder.up.1.block.1.norm2.weight", "decoder.up.1.block.1.norm2.bias", "decoder.up.1.block.1.conv2.weight", "decoder.up.1.block.1.conv2.bias", "decoder.up.1.block.2.norm1.weight", "decoder.up.1.block.2.norm1.bias", "decoder.up.1.block.2.conv1.weight", "decoder.up.1.block.2.conv1.bias", "decoder.up.1.block.2.norm2.weight", "decoder.up.1.block.2.norm2.bias", "decoder.up.1.block.2.conv2.weight", "decoder.up.1.block.2.conv2.bias", "decoder.up.1.upsample.conv.weight", "decoder.up.1.upsample.conv.bias", "decoder.up.2.block.0.norm1.weight", "decoder.up.2.block.0.norm1.bias", "decoder.up.2.block.0.conv1.weight", "decoder.up.2.block.0.conv1.bias", "decoder.up.2.block.0.norm2.weight", "decoder.up.2.block.0.norm2.bias", "decoder.up.2.block.0.conv2.weight", "decoder.up.2.block.0.conv2.bias", "decoder.up.2.block.1.norm1.weight", "decoder.up.2.block.1.norm1.bias", "decoder.up.2.block.1.conv1.weight", "decoder.up.2.block.1.conv1.bias", "decoder.up.2.block.1.norm2.weight", "decoder.up.2.block.1.norm2.bias", "decoder.up.2.block.1.conv2.weight", "decoder.up.2.block.1.conv2.bias", "decoder.up.2.block.2.norm1.weight", "decoder.up.2.block.2.norm1.bias", "decoder.up.2.block.2.conv1.weight", "decoder.up.2.block.2.conv1.bias", "decoder.up.2.block.2.norm2.weight", "decoder.up.2.block.2.norm2.bias", "decoder.up.2.block.2.conv2.weight", "decoder.up.2.block.2.conv2.bias", "decoder.up.2.upsample.conv.weight", "decoder.up.2.upsample.conv.bias", "decoder.up.3.block.0.norm1.weight", "decoder.up.3.block.0.norm1.bias", "decoder.up.3.block.0.conv1.weight", "decoder.up.3.block.0.conv1.bias", "decoder.up.3.block.0.norm2.weight", "decoder.up.3.block.0.norm2.bias", "decoder.up.3.block.0.conv2.weight", "decoder.up.3.block.0.conv2.bias", "decoder.up.3.block.1.norm1.weight", "decoder.up.3.block.1.norm1.bias", "decoder.up.3.block.1.conv1.weight", "decoder.up.3.block.1.conv1.bias", "decoder.up.3.block.1.norm2.weight", "decoder.up.3.block.1.norm2.bias", "decoder.up.3.block.1.conv2.weight", "decoder.up.3.block.1.conv2.bias", "decoder.up.3.block.2.norm1.weight", "decoder.up.3.block.2.norm1.bias", "decoder.up.3.block.2.conv1.weight", "decoder.up.3.block.2.conv1.bias", "decoder.up.3.block.2.norm2.weight", "decoder.up.3.block.2.norm2.bias", "decoder.up.3.block.2.conv2.weight", "decoder.up.3.block.2.conv2.bias", "decoder.up.3.upsample.conv.weight", "decoder.up.3.upsample.conv.bias", "decoder.norm_out.weight", "decoder.norm_out.bias". 
    Unexpected key(s) in state_dict: "encoder.conv_norm_out.bias", "encoder.conv_norm_out.weight", "encoder.down_blocks.0.downsamplers.0.conv.bias", "encoder.down_blocks.0.downsamplers.0.conv.weight", "encoder.down_blocks.0.resnets.0.conv1.bias", "encoder.down_blocks.0.resnets.0.conv1.weight", "encoder.down_blocks.0.resnets.0.conv2.bias", "encoder.down_blocks.0.resnets.0.conv2.weight", "encoder.down_blocks.0.resnets.0.norm1.bias", "encoder.down_blocks.0.resnets.0.norm1.weight", "encoder.down_blocks.0.resnets.0.norm2.bias", "encoder.down_blocks.0.resnets.0.norm2.weight", "encoder.down_blocks.0.resnets.1.conv1.bias", "encoder.down_blocks.0.resnets.1.conv1.weight", "encoder.down_blocks.0.resnets.1.conv2.bias", "encoder.down_blocks.0.resnets.1.conv2.weight", "encoder.down_blocks.0.resnets.1.norm1.bias", "encoder.down_blocks.0.resnets.1.norm1.weight", "encoder.down_blocks.0.resnets.1.norm2.bias", "encoder.down_blocks.0.resnets.1.norm2.weight", "encoder.down_blocks.1.downsamplers.0.conv.bias", "encoder.down_blocks.1.downsamplers.0.conv.weight", "encoder.down_blocks.1.resnets.0.conv1.bias", "encoder.down_blocks.1.resnets.0.conv1.weight", "encoder.down_blocks.1.resnets.0.conv2.bias", "encoder.down_blocks.1.resnets.0.conv2.weight", "encoder.down_blocks.1.resnets.0.conv_shortcut.bias", "encoder.down_blocks.1.resnets.0.conv_shortcut.weight", "encoder.down_blocks.1.resnets.0.norm1.bias", "encoder.down_blocks.1.resnets.0.norm1.weight", "encoder.down_blocks.1.resnets.0.norm2.bias", "encoder.down_blocks.1.resnets.0.norm2.weight", "encoder.down_blocks.1.resnets.1.conv1.bias", "encoder.down_blocks.1.resnets.1.conv1.weight", "encoder.down_blocks.1.resnets.1.conv2.bias", "encoder.down_blocks.1.resnets.1.conv2.weight", "encoder.down_blocks.1.resnets.1.norm1.bias", "encoder.down_blocks.1.resnets.1.norm1.weight", "encoder.down_blocks.1.resnets.1.norm2.bias", "encoder.down_blocks.1.resnets.1.norm2.weight", "encoder.down_blocks.2.downsamplers.0.conv.bias", "encoder.down_blocks.2.downsamplers.0.conv.weight", "encoder.down_blocks.2.resnets.0.conv1.bias", "encoder.down_blocks.2.resnets.0.conv1.weight", "encoder.down_blocks.2.resnets.0.conv2.bias", "encoder.down_blocks.2.resnets.0.conv2.weight", "encoder.down_blocks.2.resnets.0.conv_shortcut.bias", "encoder.down_blocks.2.resnets.0.conv_shortcut.weight", "encoder.down_blocks.2.resnets.0.norm1.bias", "encoder.down_blocks.2.resnets.0.norm1.weight", "encoder.down_blocks.2.resnets.0.norm2.bias", "encoder.down_blocks.2.resnets.0.norm2.weight", "encoder.down_blocks.2.resnets.1.conv1.bias", "encoder.down_blocks.2.resnets.1.conv1.weight", "encoder.down_blocks.2.resnets.1.conv2.bias", "encoder.down_blocks.2.resnets.1.conv2.weight", "encoder.down_blocks.2.resnets.1.norm1.bias", "encoder.down_blocks.2.resnets.1.norm1.weight", "encoder.down_blocks.2.resnets.1.norm2.bias", "encoder.down_blocks.2.resnets.1.norm2.weight", "encoder.down_blocks.3.resnets.0.conv1.bias", "encoder.down_blocks.3.resnets.0.conv1.weight", "encoder.down_blocks.3.resnets.0.conv2.bias", "encoder.down_blocks.3.resnets.0.conv2.weight", "encoder.down_blocks.3.resnets.0.norm1.bias", "encoder.down_blocks.3.resnets.0.norm1.weight", "encoder.down_blocks.3.resnets.0.norm2.bias", "encoder.down_blocks.3.resnets.0.norm2.weight", "encoder.down_blocks.3.resnets.1.conv1.bias", "encoder.down_blocks.3.resnets.1.conv1.weight", "encoder.down_blocks.3.resnets.1.conv2.bias", "encoder.down_blocks.3.resnets.1.conv2.weight", "encoder.down_blocks.3.resnets.1.norm1.bias", "encoder.down_blocks.3.resnets.1.norm1.weight", "encoder.down_blocks.3.resnets.1.norm2.bias", "encoder.down_blocks.3.resnets.1.norm2.weight", "encoder.mid_block.attentions.0.group_norm.bias", "encoder.mid_block.attentions.0.group_norm.weight", "encoder.mid_block.attentions.0.key.bias", "encoder.mid_block.attentions.0.key.weight", "encoder.mid_block.attentions.0.proj_attn.bias", "encoder.mid_block.attentions.0.proj_attn.weight", "encoder.mid_block.attentions.0.query.bias", "encoder.mid_block.attentions.0.query.weight", "encoder.mid_block.attentions.0.value.bias", "encoder.mid_block.attentions.0.value.weight", "encoder.mid_block.resnets.0.conv1.bias", "encoder.mid_block.resnets.0.conv1.weight", "encoder.mid_block.resnets.0.conv2.bias", "encoder.mid_block.resnets.0.conv2.weight", "encoder.mid_block.resnets.0.norm1.bias", "encoder.mid_block.resnets.0.norm1.weight", "encoder.mid_block.resnets.0.norm2.bias", "encoder.mid_block.resnets.0.norm2.weight", "encoder.mid_block.resnets.1.conv1.bias", "encoder.mid_block.resnets.1.conv1.weight", "encoder.mid_block.resnets.1.conv2.bias", "encoder.mid_block.resnets.1.conv2.weight", "encoder.mid_block.resnets.1.norm1.bias", "encoder.mid_block.resnets.1.norm1.weight", "encoder.mid_block.resnets.1.norm2.bias", "encoder.mid_block.resnets.1.norm2.weight", "decoder.conv_norm_out.bias", "decoder.conv_norm_out.weight", "decoder.mid_block.attentions.0.group_norm.bias", "decoder.mid_block.attentions.0.group_norm.weight", "decoder.mid_block.attentions.0.key.bias", "decoder.mid_block.attentions.0.key.weight", "decoder.mid_block.attentions.0.proj_attn.bias", "decoder.mid_block.attentions.0.proj_attn.weight", "decoder.mid_block.attentions.0.query.bias", "decoder.mid_block.attentions.0.query.weight", "decoder.mid_block.attentions.0.value.bias", "decoder.mid_block.attentions.0.value.weight", "decoder.mid_block.resnets.0.conv1.bias", "decoder.mid_block.resnets.0.conv1.weight", "decoder.mid_block.resnets.0.conv2.bias", "decoder.mid_block.resnets.0.conv2.weight", "decoder.mid_block.resnets.0.norm1.bias", "decoder.mid_block.resnets.0.norm1.weight", "decoder.mid_block.resnets.0.norm2.bias", "decoder.mid_block.resnets.0.norm2.weight", "decoder.mid_block.resnets.1.conv1.bias", "decoder.mid_block.resnets.1.conv1.weight", "decoder.mid_block.resnets.1.conv2.bias", "decoder.mid_block.resnets.1.conv2.weight", 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Additional information

No response

ClashSAN commented 1 year ago

.vae.safetensors? Try fp16 vaes, and fp32 vaes, do you get this with 1.X models too?

Bammargiela commented 1 year ago

I tried the fp16 version and it didn't work. I also tried the the fp16 and the other ones on a 1.5 model and it gave the same error.

This is the VAE that I have that works: https://huggingface.co/stabilityai/sd-vae-ft-mse-original/tree/main

Sakura-Luna commented 1 year ago

According to the error log, the problem does not seem to be on the WebUI, but there is a method you can try, assign all the variables in the following code to None, and then delete the repositories folder under the WebUI. https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/5ab7f213bec2f816f9c5644becb32eb72c8ffb89/launch.py#L239-L243

Bammargiela commented 1 year ago

Thanks. I did that and then when I run the Colab cell again it puts the hashes back in the launch.py and downloads the repositories folder again. I commented the lines out that do that but then it throws some more errors. Is it likely a problem with the Colab I'm using?

xianweicui commented 12 months ago

@Bammargiela I also encountered the same problem, how did you solve it?

kaosbeat commented 8 months ago

same problem here, when using the SDXL inpainting model. I'm doing something wrong, cause yesterday it worked Problems with both fp16 and regular version. No problems with non inpainting models. I get the same error whether I selecting the VAE from the dropdown or when naming my file modelname.vae.safetensorsor modelname.fp16.vae.safetensors and putting it next to the Version: v1.8.0 Commit hash: bef51aed032c0aaa5cfd80445bc4cf0d85b408b5

any ideas on fixing this? trying to use SDXL in openoutpaint, it worked beautifully yesterday, now I cannot even do normal txt2img/img2img
I get noise