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Add an option for faster low quality previews
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extensions to override it
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Commit eba60a4 is what is causing this error, delete the length check in sd_model starting at line 115 and it's fine.
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5971#issuecomment-1364507379
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fix: fallback model_checkpoint if it's empty
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This fixes the following error when SD attempts to start with a deleted checkpoint:
```
Traceback (most recent call last):
File "D:\Web\stable-diffusion-webui\launch.py", line 295, in <module>
start()
File "D:\Web\stable-diffusion-webui\launch.py", line 290, in start
webui.webui()
File "D:\Web\stable-diffusion-webui\webui.py", line 132, in webui
initialize()
File "D:\Web\stable-diffusion-webui\webui.py", line 62, in initialize
modules.sd_models.load_model()
File "D:\Web\stable-diffusion-webui\modules\sd_models.py", line 283, in load_model
checkpoint_info = checkpoint_info or select_checkpoint()
File "D:\Web\stable-diffusion-webui\modules\sd_models.py", line 117, in select_checkpoint
checkpoint_info = checkpoints_list.get(model_checkpoint, None)
TypeError: unhashable type: 'list'
```
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API endpoint to refresh checkpoints
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API endpoint to refresh checkpoints
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Better should_hijack_inpainting detection
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Save hypernetwork hash and fix hypernetwork parameter restoring
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Add latent upscale option to img2img
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Recently, the option to do latent upscale was added to txt2img highres
fix. This feature runs by scaling the latent sample of the image, and
then running a second pass of img2img.
But, in this edition of highres fix, the image and parameters cannot be
changed between the first pass and second pass. We might want to do a
fixup in img2img before doing the second pass, or might want to run the
second pass at a different resolution.
This change adds the option for img2img to perform its upscale in latent
space, rather than image space, giving very similar results to highres
fix with latent upscale. The result is not exactly the same because
there is an additional latent -> decoder -> image -> encoder -> latent
that won't happen in highres fix, but this conversion has relatively
small losses
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Dirty fix for missing PIL supported file extensions
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Format singleton comparisons
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feat(api): add override_settings_restore_afterwards
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Fix various typos
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Better support for 2.0-inpainting and 2.0-depth special models
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and all configs except v1-inpainting-inference.yaml already correctly set it to False)
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inpainting model
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Improve img2img color correction by performing a luminosity blend
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Prevent overlapping in X/Y plot by changing font size
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This prevents scenarios where text without line breaks will start overlapping with each other when generating X/Y plots. This is most evident when generating X/Y plots with checkpoints, as most don't contain spaces and sometimes include extra information such as the epoch, making it extra long.
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Add option to save upscaler to filename suffix in extras tab.
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Fix docker tmp/ and extensions/ handling for docker.
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symlinks
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add an option to samplers for skipping next to last sigma
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Add a workaround patch for DPM2 a issue
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DPM2 a and DPM2 a Karras samplers are both affected by an issue described by https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/3483 and can be resolved by a workaround suggested by the k-diffusion author at https://github.com/crowsonkb/k-diffusion/issues/43#issuecomment-1305195666
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Training fixes for MPS
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When saving training results with torch.save(), an exception is thrown:
"RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead."
So for MPS, check if Tensor.requires_grad and detach() if necessary.
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