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Settings to select VAE
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@@ -14,7 +14,7 @@ import modules.memmon
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import modules.sd_models
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import modules.styles
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import modules.devices as devices
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from modules import sd_samplers, sd_models, localization
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from modules import sd_samplers, sd_models, localization, sd_vae
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from modules.hypernetworks import hypernetwork
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from modules.paths import models_path, script_path, sd_path
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@@ -295,6 +295,7 @@ options_templates.update(options_section(('training', "Training"), {
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options_templates.update(options_section(('sd', "Stable Diffusion"), {
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"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
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"sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
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"sd_vae": OptionInfo("auto", "SD VAE", gr.Dropdown, lambda: {"choices": list(sd_vae.vae_list)}, refresh=sd_vae.refresh_vae_list),
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"sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
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"sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
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"inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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@@ -407,11 +408,12 @@ class Options:
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if bad_settings > 0:
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print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr)
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def onchange(self, key, func):
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def onchange(self, key, func, call=True):
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item = self.data_labels.get(key)
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item.onchange = func
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func()
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if call:
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func()
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def dumpjson(self):
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d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()}
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