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https://github.com/lllyasviel/stable-diffusion-webui-forge.git
synced 2026-02-09 01:19:58 +00:00
cleanup codes
This commit is contained in:
layerdiffusion
@@ -23,30 +23,32 @@ class ScriptRefiner(scripts.ScriptBuiltinUI):
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with InputAccordion(False, label="Refiner", elem_id=self.elem_id("enable")) as enable_refiner:
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gr.Markdown('Refiner is currently under maintenance and unavailable. Sorry for the inconvenience.')
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with gr.Row():
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refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=["", *sd_models.checkpoint_tiles()], value='', tooltip="switch to another model in the middle of generation", interactive=False, visible=False)
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# create_refresh_button(refiner_checkpoint, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, self.elem_id("checkpoint_refresh"))
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#
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# with gr.Row():
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# refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=["", *sd_models.checkpoint_tiles()], value='', tooltip="switch to another model in the middle of generation", interactive=False, visible=False)
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# # create_refresh_button(refiner_checkpoint, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, self.elem_id("checkpoint_refresh"))
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#
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# refiner_switch_at = gr.Slider(value=0.8, label="Switch at", minimum=0.01, maximum=1.0, step=0.01, elem_id=self.elem_id("switch_at"), tooltip="fraction of sampling steps when the switch to refiner model should happen; 1=never, 0.5=switch in the middle of generation", interactive=False, visible=False)
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#
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# def lookup_checkpoint(title):
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# info = sd_models.get_closet_checkpoint_match(title)
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# return None if info is None else info.title
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#
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# self.infotext_fields = [
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# PasteField(enable_refiner, lambda d: 'Refiner' in d),
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# PasteField(refiner_checkpoint, lambda d: lookup_checkpoint(d.get('Refiner')), api="refiner_checkpoint"),
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# PasteField(refiner_switch_at, 'Refiner switch at', api="refiner_switch_at"),
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# ]
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refiner_switch_at = gr.Slider(value=0.8, label="Switch at", minimum=0.01, maximum=1.0, step=0.01, elem_id=self.elem_id("switch_at"), tooltip="fraction of sampling steps when the switch to refiner model should happen; 1=never, 0.5=switch in the middle of generation", interactive=False, visible=False)
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return [enable_refiner] # , refiner_checkpoint, refiner_switch_at
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def lookup_checkpoint(title):
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info = sd_models.get_closet_checkpoint_match(title)
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return None if info is None else info.title
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self.infotext_fields = [
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PasteField(enable_refiner, lambda d: 'Refiner' in d),
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PasteField(refiner_checkpoint, lambda d: lookup_checkpoint(d.get('Refiner')), api="refiner_checkpoint"),
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PasteField(refiner_switch_at, 'Refiner switch at', api="refiner_switch_at"),
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]
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return enable_refiner, refiner_checkpoint, refiner_switch_at
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def setup(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at):
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# the actual implementation is in sd_samplers_common.py, apply_refiner
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if not enable_refiner or refiner_checkpoint in (None, "", "None"):
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p.refiner_checkpoint = None
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p.refiner_switch_at = None
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else:
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p.refiner_checkpoint = refiner_checkpoint
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p.refiner_switch_at = refiner_switch_at
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def setup(self, p, enable_refiner):
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pass
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# # the actual implementation is in sd_samplers_common.py, apply_refiner
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#
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# if not enable_refiner or refiner_checkpoint in (None, "", "None"):
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# p.refiner_checkpoint = None
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# p.refiner_switch_at = None
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# else:
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# p.refiner_checkpoint = refiner_checkpoint
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# p.refiner_switch_at = refiner_switch_at
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@@ -168,9 +168,9 @@ class CFGDenoiser(torch.nn.Module):
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x = x * (((real_sigma ** 2.0 + real_sigma_data ** 2.0) ** 0.5)[:, None, None, None])
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sigma = real_sigma
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if sd_samplers_common.apply_refiner(self, x):
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cond = self.sampler.sampler_extra_args['cond']
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uncond = self.sampler.sampler_extra_args['uncond']
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# if sd_samplers_common.apply_refiner(self, x):
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# cond = self.sampler.sampler_extra_args['cond']
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# uncond = self.sampler.sampler_extra_args['uncond']
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cond_composition, cond = prompt_parser.reconstruct_multicond_batch(cond, self.step)
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uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step) if uncond is not None else None
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@@ -161,44 +161,45 @@ replace_torchsde_browinan()
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def apply_refiner(cfg_denoiser, x):
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completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
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refiner_switch_at = cfg_denoiser.p.refiner_switch_at
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refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
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if refiner_switch_at is not None and completed_ratio < refiner_switch_at:
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return False
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if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
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return False
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if getattr(cfg_denoiser.p, "enable_hr", False):
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is_second_pass = cfg_denoiser.p.is_hr_pass
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if opts.hires_fix_refiner_pass == "first pass" and is_second_pass:
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return False
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if opts.hires_fix_refiner_pass == "second pass" and not is_second_pass:
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return False
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if opts.hires_fix_refiner_pass != "second pass":
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cfg_denoiser.p.extra_generation_params['Hires refiner'] = opts.hires_fix_refiner_pass
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cfg_denoiser.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
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cfg_denoiser.p.extra_generation_params['Refiner switch at'] = refiner_switch_at
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sampling_cleanup(sd_models.model_data.get_sd_model().forge_objects.unet)
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with sd_models.SkipWritingToConfig():
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sd_models.reload_model_weights(info=refiner_checkpoint_info)
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if not cfg_denoiser.p.disable_extra_networks:
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extra_networks.activate(cfg_denoiser.p, cfg_denoiser.p.extra_network_data)
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cfg_denoiser.p.setup_conds()
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cfg_denoiser.update_inner_model()
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sampling_prepare(sd_models.model_data.get_sd_model().forge_objects.unet, x=x)
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return True
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# completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
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# refiner_switch_at = cfg_denoiser.p.refiner_switch_at
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# refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
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#
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# if refiner_switch_at is not None and completed_ratio < refiner_switch_at:
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# return False
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#
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# if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
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# return False
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#
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# if getattr(cfg_denoiser.p, "enable_hr", False):
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# is_second_pass = cfg_denoiser.p.is_hr_pass
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#
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# if opts.hires_fix_refiner_pass == "first pass" and is_second_pass:
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# return False
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#
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# if opts.hires_fix_refiner_pass == "second pass" and not is_second_pass:
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# return False
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#
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# if opts.hires_fix_refiner_pass != "second pass":
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# cfg_denoiser.p.extra_generation_params['Hires refiner'] = opts.hires_fix_refiner_pass
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#
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# cfg_denoiser.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
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# cfg_denoiser.p.extra_generation_params['Refiner switch at'] = refiner_switch_at
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#
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# sampling_cleanup(sd_models.model_data.get_sd_model().forge_objects.unet)
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#
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# with sd_models.SkipWritingToConfig():
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# sd_models.reload_model_weights(info=refiner_checkpoint_info)
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#
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# if not cfg_denoiser.p.disable_extra_networks:
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# extra_networks.activate(cfg_denoiser.p, cfg_denoiser.p.extra_network_data)
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#
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# cfg_denoiser.p.setup_conds()
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# cfg_denoiser.update_inner_model()
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#
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# sampling_prepare(sd_models.model_data.get_sd_model().forge_objects.unet, x=x)
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# return True
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pass
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class TorchHijack:
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