mirror of
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38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
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def realesrgan_models_names():
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import modules.realesrgan_model
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return [x.name for x in modules.realesrgan_model.get_realesrgan_models(None)]
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def postprocessing_scripts():
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import modules.scripts
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return modules.scripts.scripts_postproc.scripts
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def sd_vae_items():
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import modules.sd_vae
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return ["Automatic", "None"] + list(modules.sd_vae.vae_dict)
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def refresh_vae_list():
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import modules.sd_vae
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modules.sd_vae.refresh_vae_list()
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def list_crossattention():
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return [
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"Disable cross-attention layer optimization",
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"xFormers",
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"Scaled-Dot-Product",
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"Doggettx's",
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"InvokeAI's",
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"Sub-quadratic",
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"Split attention"
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]
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# parser.add_argument("--sub-quad-q-chunk-size", type=int, help="query chunk size for the sub-quadratic cross-attention layer optimization to use", default=1024)
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# parser.add_argument("--sub-quad-kv-chunk-size", type=int, help="kv chunk size for the sub-quadratic cross-attention layer optimization to use", default=None)
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# parser.add_argument("--sub-quad-chunk-threshold", type=int, help="the percentage of VRAM threshold for the sub-quadratic cross-attention layer optimization to use chunking", default=None)
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