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makecheckbox(images_tab, "Use TAE SD (AutoFix Broken VAE)", sd_vaeauto_var, 42,command=toggletaesd,tooltiptxt="Replace VAE with TAESD. May fix bad VAE.")
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makecheckbox(images_tab, "TAE SD (AutoFix Broken VAE)", sd_vaeauto_var, 42,command=toggletaesd,tooltiptxt="Replace VAE with TAESD. May fix bad VAE.")
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makecheckbox(images_tab, "Conv2D Direct for VAE", sd_vae_convdir_var, 42, padx=220, tooltiptxt="Enable Conv2D Direct for VAE. Saves memory and improves performance.\nMight crash if not supported by the backend.")
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makelabelentry(images_tab, "VAE Tiling Threshold:", sd_tiled_vae_var, 44, 50, padx=144,singleline=True,tooltip="Enable VAE Tiling for images above this size, to save memory.\nSet to 0 to disable VAE tiling.")
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makecheckbox(images_tab, "Flash Attention", sd_flash_attention_var, 48, tooltiptxt="Enable Flash Attention for diffusion. May save memory or improve performance.")
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@@ -5580,6 +5584,8 @@ def export_vars():
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args.sdvae=""
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ifsd_vae_var.get() !="":
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args.sdvae=sd_vae_var.get()
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ifsd_vae_convdir_var.get()==1:
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args.sdvaeconvdir=True
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ifsd_t5xxl_var.get() !="":
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args.sdt5xxl=sd_t5xxl_var.get()
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ifsd_clipl_var.get() !="":
@@ -5808,6 +5814,7 @@ def import_vars(dict):
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sd_photomaker_var.set(dict["sdphotomaker"] if ("sdphotomaker"indictanddict["sdphotomaker"]) else"")
sdparsergroupvae.add_argument("--sdvae", metavar=('[filename]'), help="Specify an image generation safetensors VAE which replaces the one in the model.", default="")
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sdparsergroupvae.add_argument("--sdvaeauto", help="Uses a built-in VAE via TAE SD, which is very fast, and fixed bad VAEs.", action='store_true')
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sdparsergroupvae.add_argument("--sdvaeconvdir", help="Enables Conv2D Direct for the image diffusion model. Should improve performance and reduce memory usage. Might crash if not supported by the backend.", action='store_true')
sdparsergrouplora.add_argument("--sdquant", help="If specified, loads the model quantized to save memory.", action='store_true')
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sdparsergrouplora.add_argument("--sdlora", metavar=('[filename]'), help="Specify an image generation LORA safetensors model to be applied.", default="")
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