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Add sdxl only arg

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Kohaku-Blueleaf 2023-10-19 23:57:22 +08:00
parent 7c128bbdac
commit 5f9ddfa46f
2 changed files with 4 additions and 0 deletions
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1
modules/cmd_args.py
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@ -119,3 +119,4 @@ parser.add_argument("--disable-all-extensions", action='store_true', help="preve
parser.add_argument("--disable-extra-extensions", action='store_true', help="prevent all extensions except built-in from running regardless of any other settings", default=False) parser.add_argument("--disable-extra-extensions", action='store_true', help="prevent all extensions except built-in from running regardless of any other settings", default=False)
parser.add_argument("--skip-load-model-at-start", action='store_true', help="if load a model at web start, only take effect when --nowebui", ) parser.add_argument("--skip-load-model-at-start", action='store_true', help="if load a model at web start, only take effect when --nowebui", )
parser.add_argument("--opt-unet-fp8-storage", action='store_true', help="use fp8 for SD UNet to save vram", default=False) parser.add_argument("--opt-unet-fp8-storage", action='store_true', help="use fp8 for SD UNet to save vram", default=False)
parser.add_argument("--opt-unet-fp8-storage-xl", action='store_true', help="use fp8 for SD UNet to save vram", default=False)

3
modules/sd_models.py
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@ -394,6 +394,9 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
if shared.cmd_opts.opt_unet_fp8_storage: if shared.cmd_opts.opt_unet_fp8_storage:
model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn) model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn)
timer.record("apply fp8 unet") timer.record("apply fp8 unet")
elif model.is_sdxl and shared.cmd_opts.opt_unet_fp8_storage_xl:
model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn)
timer.record("apply fp8 unet for sdxl")
devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16 devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16