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Merge pull request #12412 from dhwz/dev

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fix typo
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AUTOMATIC1111 2023-08-08 23:30:57 +03:00 committed by GitHub
commit a2360de3f3
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2 changed files with 2 additions and 2 deletions
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2
modules/processing.py
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@ -568,7 +568,7 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False):
errors.print_error_explanation( errors.print_error_explanation(
"A tensor with all NaNs was produced in VAE.\n" "A tensor with all NaNs was produced in VAE.\n"
"Web UI will now convert VAE into 32-bit float and retry.\n" "Web UI will now convert VAE into 32-bit float and retry.\n"
"To disable this behavior, disable the 'Automaticlly revert VAE to 32-bit floats' setting.\n" "To disable this behavior, disable the 'Automatically revert VAE to 32-bit floats' setting.\n"
"To always start with 32-bit VAE, use --no-half-vae commandline flag." "To always start with 32-bit VAE, use --no-half-vae commandline flag."
) )

2
modules/shared.py
View File

@ -481,7 +481,7 @@ For img2img, VAE is used to process user's input image before the sampling, and
"sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
"sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"),
"sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"),
"auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "auto_vae_precision": OptionInfo(True, "Automatically revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"),
"sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"),
"sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"),
})) }))