mirror of https://github.com/vladmandic/automatic
remove split-attention and add attention slicing option
Signed-off-by: Vladimir Mandic <mandic00@live.com>pull/4236/head
Vladimir Mandic
parent
1b45c145e9
commit
eb025eaf31
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@ -55,6 +55,8 @@
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- replace `pynvml` with `nvidia-ml-py` for gpu monitoring
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- update **loopback** script with radon seed option, thanks @rabanti
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- **vae** slicing enable for lowvram/medvram, tiling for lowvram, both disabled otherwise
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- **attention** remove split-attention and add explicitly attention slicing enable/disable option
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can be combined with sdp, enabling may improve stability when used on iGPU or shared memory systems
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- **Fixes**
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- ui: fix image metadata display when switching selected image in control tab
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- framepack: add explicit hf-login before framepack load
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@ -0,0 +1,20 @@
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const guiders = {
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None: '',
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'LSC: LayerSkipConfig': 'https://github.com/huggingface/diffusers/blob/041501aea92919c9c7f36e189fc9cf7d865ebb96/src/diffusers/hooks/layer_skip.py#L41',
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'CFG: ClassifierFreeGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.ClassifierFreeGuidance',
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'Auto: AutoGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.AutoGuidance',
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'Zero: ClassifierFreeZeroStar': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.ClassifierFreeZeroStarGuidance',
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'PAG: PerturbedAttentionGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.PerturbedAttentionGuidance',
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'APG: AdaptiveProjectedGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.AdaptiveProjectedGuidance',
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'SLG: SkipLayerGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.SkipLayerGuidance',
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'SEG: SmoothedEnergyGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.SmoothedEnergyGuidance',
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'TCFG: TangentialClassifierFreeGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.TangentialClassifierFreeGuidance',
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'FDG: FrequencyDecoupledGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.FrequencyDecoupledGuidance',
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};
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function getGuidanceDocs(guider) {
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if (guider.label) guider = guider.label;
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const url = guiders[guider];
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log('getGuidanceDocs', guider, url);
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if (url) window.open(url, '_blank');
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}
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@ -255,6 +255,7 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
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prompt: str = '', negative_prompt: str = '', styles: List[str] = [],
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steps: int = 20, sampler_index: int = None,
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seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1,
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guidance_name: str = 'Default', guidance_scale: float = 6.0, guidance_rescale: float = 0.0, guidance_start: float = 0.0, guidance_stop: float = 1.0,
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cfg_scale: float = 6.0, clip_skip: float = 1.0, image_cfg_scale: float = 6.0, diffusers_guidance_rescale: float = 0.7, pag_scale: float = 0.0, pag_adaptive: float = 0.5, cfg_end: float = 1.0,
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vae_type: str = 'Full', tiling: bool = False, hidiffusion: bool = False,
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detailer_enabled: bool = True, detailer_prompt: str = '', detailer_negative: str = '', detailer_steps: int = 10, detailer_strength: float = 0.3, detailer_resolution: int = 1024,
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@ -306,7 +307,13 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
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seed_resize_from_h = seed_resize_from_h,
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seed_resize_from_w = seed_resize_from_w,
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denoising_strength = denoising_strength,
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# advanced
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# modular guidance
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guidance_name = guidance_name,
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guidance_scale = guidance_scale,
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guidance_rescale = guidance_rescale,
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guidance_start = guidance_start,
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guidance_stop = guidance_stop,
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# legacy guidance
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cfg_scale = cfg_scale,
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cfg_end = cfg_end,
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clip_skip = clip_skip,
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@ -314,6 +321,7 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
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diffusers_guidance_rescale = diffusers_guidance_rescale,
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pag_scale = pag_scale,
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pag_adaptive = pag_adaptive,
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# advanced
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vae_type = vae_type,
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tiling = tiling,
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hidiffusion = hidiffusion,
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@ -161,10 +161,8 @@ def img2img(id_task: str, state: str, mode: int,
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vae_type, tiling, hidiffusion,
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detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
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n_iter, batch_size,
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cfg_scale, image_cfg_scale,
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diffusers_guidance_rescale,
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pag_scale, pag_adaptive,
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cfg_end,
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
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refiner_start,
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clip_skip,
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denoising_strength,
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@ -255,6 +253,11 @@ def img2img(id_task: str, state: str, mode: int,
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batch_size=batch_size,
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n_iter=n_iter,
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steps=steps,
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guidance_name=guidance_name,
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guidance_scale=guidance_scale,
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guidance_rescale=guidance_rescale,
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guidance_start=guidance_start,
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guidance_stop=guidance_stop,
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cfg_scale=cfg_scale,
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cfg_end=cfg_end,
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clip_skip=clip_skip,
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@ -0,0 +1,87 @@
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import diffusers
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from modules import shared, errors, processing
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# ['Default', 'CFG', 'Zero', 'PAG', 'APG', 'SLG', 'SEG', 'TCFG', 'FDG']
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guiders = {
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# 'None': { 'cls': None, 'args': {}, },
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'Default': { 'cls': None, 'args': {}, },
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'CFG: ClassifierFreeGuidance': { 'cls': diffusers.ClassifierFreeGuidance, 'args': {} },
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'Auto: AutoGuidance': { 'cls': diffusers.AutoGuidance, 'args': { 'dropout': 1.0, 'auto_guidance_layers': [7, 8, 9], 'auto_guidance_config': None } },
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'Zero: ClassifierFreeZeroStar': { 'cls': diffusers.ClassifierFreeZeroStarGuidance, 'args': { 'zero_init_steps': 1 } },
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'PAG: PerturbedAttentionGuidance': { 'cls': diffusers.PerturbedAttentionGuidance, 'args': { 'perturbed_guidance_scale': 2.8, 'perturbed_guidance_start': 0.01, 'perturbed_guidance_stop': 0.2, 'perturbed_guidance_layers': [7, 8, 9], 'perturbed_guidance_config': None } },
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'APG: AdaptiveProjectedGuidance': { 'cls': diffusers.AdaptiveProjectedGuidance, 'args': { 'adaptive_projected_guidance_momentum': -1, 'adaptive_projected_guidance_rescale': 15.0 } },
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'SLG: SkipLayerGuidance': { 'cls': diffusers.SkipLayerGuidance, 'args': { 'skip_layer_guidance_scale': 2.8, 'skip_layer_guidance_start': 0.01, 'skip_layer_guidance_stop': 0.2, 'skip_layer_guidance_layers': [7, 8, 9], 'skip_layer_config': None } },
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'SEG: SmoothedEnergyGuidance': { 'cls': diffusers.SmoothedEnergyGuidance, 'args': { 'seg_guidance_scale': 3.0, 'seg_blur_sigma': 9999999.0, 'seg_blur_threshold_inf': 9999.0, 'seg_guidance_start': 0.0, 'seg_guidance_stop': 1.0, 'seg_guidance_layers': [7, 8, 9], 'seg_guidance_config': None } },
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'TCFG: TangentialClassifierFreeGuidance': { 'cls': diffusers.TangentialClassifierFreeGuidance, 'args': {} },
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'FDG: FrequencyDecoupledGuidance': { 'cls': diffusers.FrequencyDecoupledGuidance, 'args': { 'guidance_scales': [10.0, 5.0], 'parallel_weights': 1.0, 'guidance_rescale_space': "data" } },
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}
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base_args = {
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'guidance_scale': 6.0,
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'guidance_rescale': 0.0,
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'start': 0.0,
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'stop': 1.0,
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}
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def set_guider(p: processing.StableDiffusionProcessing):
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guidance_name = p.guidance_name or 'Default'
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if guidance_name not in guiders:
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return None
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if guidance_name == 'Default':
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if hasattr(shared.sd_model, 'default_guider'):
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guider_info = shared.sd_model.default_guider
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shared.sd_model.update_components(guider=guider_info)
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else:
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guider_info = shared.sd_model.get_component_spec("guider")
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shared.sd_model.default_guider = guider_info
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guider_cls = guider_info.type_hint
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if guider_info is not None and guider_cls is not None and guider_info.config is not None:
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guider_args = {k: v for k, v in guider_info.config.items() if not k.startswith('_') and v is not None}
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else:
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guider_args = {}
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shared.log.info(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args}')
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return
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if guidance_name == 'None':
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shared.sd_model.update_components(guider=None) # breaks the pipeline
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shared.log.info(f'Guider: name={guidance_name}')
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return
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guider_info = guiders[guidance_name]
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guider_cls = guider_info['cls']
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guider_args = {}
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for k, v in base_args.items():
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if v is not None and v >= 0.0:
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guider_args[k] = v
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shared.log.warning('Guiders: partially implemented') # TODO: guiders
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for k, v in guider_info['args'].items():
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try:
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if k is None:
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pass
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elif k.endswith('_layers') and isinstance(v, str):
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guider_args[k] = [int(x.strip()) for x in v.split(',') if x.strip().isdigit()]
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elif k.endswith('_config'):
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# if lsc_enabled
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# guider_args[k] = diffusers.LayerSkipConfig(...)
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pass
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elif isinstance(v, list) and len(v) > 0:
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guider_args[k] = v
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elif isinstance(v, int) and (v >= 0):
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guider_args[k] = int(v)
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elif isinstance(v, float) and (v >= 0.0):
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guider_args[k] = float(v)
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elif isinstance(v, str) and (len(v) > 0):
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guider_args[k] = v
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except Exception as e:
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shared.log.error(f'Guiders: arg={k} value={v} error={e}')
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errors.display(e, 'Guiders')
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# guider_args.update(guider_info['args'])
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if guider_cls is not None:
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try:
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guider_instance = guider_cls(**guider_args)
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shared.log.info(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args}')
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shared.sd_model.update_components(guider=guider_instance)
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except Exception as e:
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shared.log.error(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args} {e}')
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return
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@ -36,7 +36,13 @@ class StableDiffusionProcessing:
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sampler_name: str = None,
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hr_sampler_name: str = None,
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eta: float = None,
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# guidance
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# modular guidance
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guidance_name: str = 'Default',
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guidance_scale: float = 6.0,
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guidance_rescale: float = 0.0,
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guidance_start: float = 0.0,
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guidance_stop: float = 1.0,
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# legacy guidance
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cfg_scale: float = 6.0,
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cfg_end: float = 1,
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diffusers_guidance_rescale: float = 0.0,
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@ -247,6 +253,11 @@ class StableDiffusionProcessing:
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self.do_not_save_grid = do_not_save_grid
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self.override_settings_restore_afterwards = override_settings_restore_afterwards
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self.eta = eta
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self.guidance_name = guidance_name
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self.guidance_scale = guidance_scale
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self.guidance_rescale = guidance_rescale
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self.guidance_start = guidance_start
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self.guidance_stop = guidance_stop
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self.cfg_scale = cfg_scale
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self.cfg_end = cfg_end
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self.diffusers_guidance_rescale = diffusers_guidance_rescale
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@ -102,6 +102,8 @@ def process_pre(p: processing.StableDiffusionProcessing):
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modular_pipe = modular.convert_to_modular(shared.sd_model)
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if modular_pipe is not None:
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shared.sd_model = modular_pipe
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from modules import modular_guiders
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modular_guiders.set_guider(p)
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timer.process.record('pre')
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@ -1070,17 +1070,19 @@ def set_diffusers_attention(pipe, quiet:bool=False):
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pipe.enable_xformers_memory_efficient_attention()
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else:
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shared.log.warning(f"Attention: xFormers is not compatible with {pipe.__class__.__name__}")
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elif shared.opts.cross_attention_optimization == "Split attention":
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if hasattr(pipe, "enable_attention_slicing"):
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pipe.enable_attention_slicing()
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else:
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shared.log.warning(f"Attention: Split attention is not compatible with {pipe.__class__.__name__}")
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elif shared.opts.cross_attention_optimization == "Batch matrix-matrix":
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set_attn(pipe, p.AttnProcessor(), name="Batch matrix-matrix")
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elif shared.opts.cross_attention_optimization == "Dynamic Attention BMM":
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from modules.sd_hijack_dynamic_atten import DynamicAttnProcessorBMM
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set_attn(pipe, DynamicAttnProcessorBMM(), name="Dynamic Attention BMM")
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if shared.opts.attention_slicing != "Default" and hasattr(pipe, "enable_attention_slicing") and hasattr(pipe, "disable_attention_slicing"):
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if shared.opts.attention_slicing:
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pipe.enable_attention_slicing()
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else:
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pipe.disable_attention_slicing()
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shared.log.debug(f"Attention: slicing={shared.opts.attention_slicing}")
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pipe.current_attn_name = shared.opts.cross_attention_optimization
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@ -290,6 +290,8 @@ options_templates.update(options_section(('cuda', "Compute Settings"), {
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"cross_attention_sep": OptionInfo("<h2>Cross Attention</h2>", "", gr.HTML),
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"cross_attention_optimization": OptionInfo(startup_cross_attention, "Attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention()}),
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"attention_": OptionInfo("<h2>Cross Attention</h2>", "", gr.HTML),
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"attention_slicing": OptionInfo('Default', "Attention slicing", gr.CheckboxGroup, {"choices": ['Default', 'Enabled', 'Disabled']}),
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"sdp_options": OptionInfo(startup_sdp_options, "SDP options", gr.CheckboxGroup, {"choices": startup_sdp_choices}),
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"xformers_options": OptionInfo(['Flash attention'], "xFormers options", gr.CheckboxGroup, {"choices": ['Flash attention'] }),
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"dynamic_attention_slice_rate": OptionInfo(0.5, "Dynamic Attention slicing rate in GB", gr.Slider, {"minimum": 0.01, "maximum": max(gpu_memory,4), "step": 0.01}),
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@ -120,7 +120,6 @@ def list_crossattention():
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"Scaled-Dot-Product",
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"xFormers",
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"Batch matrix-matrix",
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"Split attention",
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"Dynamic Attention BMM"
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]
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@ -14,6 +14,7 @@ def txt2img(id_task, state,
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vae_type, tiling, hidiffusion,
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detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
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n_iter, batch_size,
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
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clip_skip,
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seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
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@ -55,6 +56,11 @@ def txt2img(id_task, state,
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batch_size=batch_size,
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n_iter=n_iter,
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steps=steps,
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guidance_name=guidance_name,
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guidance_scale=guidance_scale,
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guidance_rescale=guidance_rescale,
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guidance_start=guidance_start,
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guidance_stop=guidance_stop,
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cfg_scale=cfg_scale,
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image_cfg_scale=image_cfg_scale,
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diffusers_guidance_rescale=diffusers_guidance_rescale,
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@ -2,7 +2,8 @@ import os
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import time
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import gradio as gr
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from modules.control import unit
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from modules import errors, shared, progress, ui_common, ui_sections, generation_parameters_copypaste, call_queue, scripts_manager, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
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from modules import errors, shared, progress, generation_parameters_copypaste, call_queue, scripts_manager, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
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from modules import ui_common, ui_sections, ui_guidance
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from modules import ui_control_helpers as helpers
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@ -156,7 +157,7 @@ def create_ui(_blocks: gr.Blocks=None):
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mask_controls = masking.create_segment_ui()
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cfg_scale, image_cfg_scale, guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('control')
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('control')
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vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('control')
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hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('control')
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@ -274,7 +275,8 @@ def create_ui(_blocks: gr.Blocks=None):
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prompt, negative, styles,
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steps, sampler_index,
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seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
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cfg_scale, clip_skip, image_cfg_scale, guidance_rescale, pag_scale, pag_adaptive, cfg_end, vae_type, tiling, hidiffusion,
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
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cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end, vae_type, tiling, hidiffusion,
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detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
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||||
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio,
|
||||
resize_mode_before, resize_name_before, resize_context_before, width_before, height_before, scale_by_before, selected_scale_tab_before,
|
||||
|
|
@ -354,14 +356,19 @@ def create_ui(_blocks: gr.Blocks=None):
|
|||
(mask_controls[4], "Mask erode"),
|
||||
(mask_controls[5], "Mask dilate"),
|
||||
(mask_controls[6], "Mask auto"),
|
||||
# guidance
|
||||
(guidance_name, "Guidance"),
|
||||
(guidance_scale, "Guidance scale"),
|
||||
(guidance_rescale, "Guidance rescale"),
|
||||
(guidance_start, "Guidance start"),
|
||||
(guidance_stop, "Guidance stop"),
|
||||
# advanced
|
||||
(cfg_scale, "Guidance scale"),
|
||||
(cfg_scale, "CFG scale"),
|
||||
(cfg_end, "CFG end"),
|
||||
(clip_skip, "Clip skip"),
|
||||
(image_cfg_scale, "Image CFG scale"),
|
||||
(image_cfg_scale, "Hires CFG scale"),
|
||||
(guidance_rescale, "CFG rescale"),
|
||||
(diffusers_guidance_rescale, "CFG rescale"),
|
||||
(vae_type, "VAE type"),
|
||||
(tiling, "Tiling"),
|
||||
(hidiffusion, "HiDiffusion"),
|
||||
|
|
|
|||
|
|
@ -0,0 +1,125 @@
|
|||
import gradio as gr
|
||||
from modules import shared, modular_guiders
|
||||
from modules import ui_symbols, ui_components
|
||||
|
||||
|
||||
def create_guidance_inputs(tab):
|
||||
with gr.Accordion(open=False, label='Guidance', elem_id=f"{tab}_guidance", elem_classes=["small-accordion"]):
|
||||
with gr.Group():
|
||||
|
||||
with gr.Row(elem_id=f"{tab}_guider_row", elem_classes=['flexbox'], visible=shared.opts.model_modular_enable):
|
||||
guidance_name = gr.Dropdown(choices=list(modular_guiders.guiders.keys()), value='Default', label='Guider', elem_id=f"{tab}_guider")
|
||||
guidance_btn = ui_components.ToolButton(value=ui_symbols.book, elem_id=f"{tab}_guider_docs")
|
||||
guidance_btn.click(fn=None, _js='getGuidanceDocs', inputs=[guidance_name], outputs=[])
|
||||
with gr.Row(visible=shared.opts.model_modular_enable):
|
||||
guidance_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_guidance_scale")
|
||||
guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance rescale', value=0.0, elem_id=f"{tab}_guidance_rescale")
|
||||
with gr.Row(visible=shared.opts.model_modular_enable):
|
||||
guidance_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance start', value=0.0, elem_id=f"{tab}_guidance_start")
|
||||
guidance_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance stop', value=1.0, elem_id=f"{tab}_guidance_stop")
|
||||
guidance_args = [guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop]
|
||||
|
||||
lsc_group = gr.Accordion(open=False, label='Layer skip guidance', elem_classes=["small-accordion"], visible=shared.opts.model_modular_enable)
|
||||
with lsc_group:
|
||||
with gr.Row():
|
||||
guidance_lsc_enabled = gr.Checkbox(label='Enable LayerSkipConfig', value=False)
|
||||
guidance_lsc_label = gr.Label(value='LSC: LayerSkipConfig', elem_id=f"{tab}_lsc_label", visible=False)
|
||||
guidance_lsc_btn = ui_components.ToolButton(value=ui_symbols.book, elem_id=f"{tab}_lsc_docs", elem_classes=["guidance-docs"])
|
||||
guidance_lsc_btn.click(fn=None, _js='getGuidanceDocs', inputs=[guidance_lsc_label], outputs=[])
|
||||
with gr.Row():
|
||||
guidance_lsc_indices = gr.Textbox(label='LSC layer indices', value='1, 2, 3', placeholder='Comma-separated layer indices to skip')
|
||||
with gr.Row():
|
||||
guidance_lsc_fqn = gr.Textbox(label='LSC fully qualified name', value='transformer_blocks', placeholder='Fully qualified name of the layer stack')
|
||||
with gr.Row():
|
||||
guidance_lsc_skip_attention = gr.Checkbox(label='LSC skip attention blocks', value=True)
|
||||
guidance_lsc_skip_ff = gr.Checkbox(label='LSC skip feed-forward blocks', value=True)
|
||||
guidance_lsc_skip_attention_scores = gr.Checkbox(label='LSC skip attention scores', value=False)
|
||||
with gr.Row():
|
||||
guidance_lsc_dropout = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='LSC dropout rate', value=1.0)
|
||||
lsc_args = [guidance_lsc_enabled, guidance_lsc_indices, guidance_lsc_fqn, guidance_lsc_skip_attention, guidance_lsc_skip_ff, guidance_lsc_skip_attention_scores, guidance_lsc_dropout]
|
||||
|
||||
auto_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with auto_group:
|
||||
guidance_auto_dropout = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='AutoGuidance dropout', value=0.1)
|
||||
guidance_auto_layers = gr.Textbox(label='AutoGuidance layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
|
||||
guidance_auto_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='AutoGuidance config')
|
||||
guidance_auto_args = [guidance_auto_dropout, guidance_auto_layers, guidance_auto_config]
|
||||
|
||||
zero_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with zero_group:
|
||||
guidance_zero_init_steps = gr.Slider(minimum=0, maximum=10, step=1, label='ZeroStar init steps', value=1)
|
||||
guidance_zero_args = [guidance_zero_init_steps]
|
||||
|
||||
pag_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with pag_group:
|
||||
guidance_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='PAG scale', value=2.8)
|
||||
guidance_pag_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='PAG start', value=0.01)
|
||||
guidance_pag_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='PAG stop', value=0.2)
|
||||
guidance_pag_layers = gr.Textbox(label='PAG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
|
||||
guidance_pag_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='PAG config')
|
||||
guidance_pag_args = [guidance_pag_scale, guidance_pag_start, guidance_pag_stop, guidance_pag_layers, guidance_pag_config]
|
||||
|
||||
apg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with apg_group:
|
||||
guidance_apg_momentum = gr.Slider(minimum=-1.0, maximum=1.0, step=0.05, label='APG momentum', value=-1.0)
|
||||
guidance_apg_rescale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='APG rescale', value=15.0)
|
||||
guidance_apg_args = [guidance_apg_momentum, guidance_apg_rescale]
|
||||
|
||||
slg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with slg_group:
|
||||
guidance_slg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='SLG scale', value=2.8)
|
||||
guidance_slg_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SLG start', value=0.01)
|
||||
guidance_slg_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SLG stop', value=0.2)
|
||||
guidance_slg_layers = gr.Textbox(label='SLG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
|
||||
guidance_slg_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='SLG config')
|
||||
guidance_slg_args = [guidance_slg_scale, guidance_slg_start, guidance_slg_stop, guidance_slg_layers, guidance_slg_config]
|
||||
|
||||
seg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with seg_group:
|
||||
guidance_seg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='SEG scale', value=3.0)
|
||||
guidance_seg_blur_sigma = gr.Number(label='SEG blur sigma', value=9999999.0)
|
||||
guidance_seg_blur_threshold_inf = gr.Number(label='SEG blur threshold inf', value=9999.0)
|
||||
guidance_seg_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SEG start', value=0.0)
|
||||
guidance_seg_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SEG stop', value=1.0)
|
||||
guidance_seg_layers = gr.Textbox(label='SEG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
|
||||
guidance_seg_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='SEG config')
|
||||
guidance_seg_args = [guidance_seg_scale, guidance_seg_blur_sigma, guidance_seg_blur_threshold_inf, guidance_seg_start, guidance_seg_stop, guidance_seg_layers, guidance_seg_config]
|
||||
|
||||
tcfg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with tcfg_group:
|
||||
pass
|
||||
|
||||
fdg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
|
||||
with fdg_group:
|
||||
guidance_fdg_scales = gr.Textbox(label='FDG scales', value='10.0, 5.0', placeholder='Comma-separated scales, e.g. 10.0,5.0')
|
||||
guidance_fdg_weights = gr.Textbox(label='FDG weights', value='1.0', placeholder='Single float or comma-separated weights, e.g. 1.0 or 1.0,0.5')
|
||||
guidance_fdg_rescale_space = gr.Dropdown(choices=['data', 'freq'], value='data', label='FDG rescale space')
|
||||
guidance_fdg_args = [guidance_fdg_scales, guidance_fdg_weights, guidance_fdg_rescale_space]
|
||||
|
||||
def adv_visibility(guidance_name):
|
||||
return [
|
||||
gr.update(visible=guidance_name.startswith('Auto')),
|
||||
gr.update(visible=guidance_name.startswith('Zero')),
|
||||
gr.update(visible=guidance_name.startswith('PAG')),
|
||||
gr.update(visible=guidance_name.startswith('APG')),
|
||||
gr.update(visible=guidance_name.startswith('SLG')),
|
||||
gr.update(visible=guidance_name.startswith('SEG')),
|
||||
gr.update(visible=guidance_name.startswith('TCFG')),
|
||||
gr.update(visible=guidance_name.startswith('FDG')),
|
||||
]
|
||||
guidance_name.change(fn=adv_visibility, inputs=[guidance_name], outputs=[auto_group, zero_group, pag_group, apg_group, slg_group, seg_group, tcfg_group, fdg_group])
|
||||
|
||||
gr.HTML(value='<br><h2>Fallback guidance</h2>', visible=shared.opts.model_modular_enable, elem_id=f"{tab}_guidance_note")
|
||||
with gr.Row(elem_id=f"{tab}_cfg_row", elem_classes=['flexbox']):
|
||||
cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_cfg_scale")
|
||||
cfg_end = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance end', value=1.0, elem_id=f"{tab}_cfg_end")
|
||||
with gr.Row():
|
||||
image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Refine guidance', value=6.0, elem_id=f"{tab}_image_cfg_scale")
|
||||
diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Rescale guidance', value=0.0, elem_id=f"{tab}_image_cfg_rescale")
|
||||
with gr.Row():
|
||||
diffusers_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='Attention guidance', value=0.0, elem_id=f"{tab}_pag_scale")
|
||||
diffusers_pag_adaptive = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Adaptive scaling', value=0.5, elem_id=f"{tab}_pag_adaptive")
|
||||
|
||||
_modular_args = guidance_args + lsc_args + guidance_auto_args + guidance_zero_args + guidance_pag_args + guidance_apg_args + guidance_slg_args + guidance_seg_args + guidance_fdg_args
|
||||
standard_args = [cfg_scale, image_cfg_scale, diffusers_guidance_rescale, diffusers_pag_scale, diffusers_pag_adaptive, cfg_end]
|
||||
return guidance_args + standard_args
|
||||
|
|
@ -1,11 +1,11 @@
|
|||
import os
|
||||
from PIL import Image
|
||||
import gradio as gr
|
||||
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
|
||||
from modules import timer, shared, ui_common, ui_sections, generation_parameters_copypaste, processing_vae
|
||||
from modules import timer, shared, call_queue, generation_parameters_copypaste, processing_vae
|
||||
from modules import ui_common, ui_sections, ui_guidance
|
||||
|
||||
|
||||
def process_interrogate(mode, ii_input_files, ii_input_dir, ii_output_dir, *ii_singles):
|
||||
import os
|
||||
from PIL import Image
|
||||
from modules.interrogate.interrogate import interrogate
|
||||
mode = int(mode)
|
||||
if mode in {0, 1, 3, 4}:
|
||||
|
|
@ -132,7 +132,7 @@ def create_ui():
|
|||
denoising_strength = gr.Slider(minimum=0.00, maximum=0.99, step=0.01, label='Denoising strength', value=0.30, elem_id="img2img_denoising_strength")
|
||||
refiner_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Denoise start', value=0.0, elem_id="img2img_refiner_start")
|
||||
|
||||
cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('img2img')
|
||||
guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('img2img')
|
||||
vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('img2img')
|
||||
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('img2img')
|
||||
enable_hr, hr_sampler_index, hr_denoising_strength, hr_resize_mode, hr_resize_context, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, hr_refiner_start, refiner_prompt, refiner_negative = ui_sections.create_hires_inputs('img2img')
|
||||
|
|
@ -177,8 +177,8 @@ def create_ui():
|
|||
vae_type, tiling, hidiffusion,
|
||||
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
|
||||
batch_count, batch_size,
|
||||
cfg_scale, image_cfg_scale,
|
||||
diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
|
||||
guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
|
||||
cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
|
||||
refiner_start,
|
||||
clip_skip,
|
||||
denoising_strength,
|
||||
|
|
@ -194,7 +194,7 @@ def create_ui():
|
|||
override_settings,
|
||||
]
|
||||
img2img_dict = dict(
|
||||
fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', ''], name='Image'),
|
||||
fn=call_queue.wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', ''], name='Image'),
|
||||
_js="submit_img2img",
|
||||
inputs= img2img_args + img2img_script_inputs,
|
||||
outputs=[
|
||||
|
|
@ -229,8 +229,8 @@ def create_ui():
|
|||
)
|
||||
interrogate_btn.click(fn=lambda *args: process_interrogate(*args), **interrogate_args)
|
||||
|
||||
img2img_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_prompt], outputs=[img2img_token_counter], show_progress = False)
|
||||
img2img_negative_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_negative_prompt], outputs=[img2img_negative_token_counter], show_progress = False)
|
||||
img2img_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_prompt], outputs=[img2img_token_counter], show_progress = False)
|
||||
img2img_negative_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_negative_prompt], outputs=[img2img_negative_token_counter], show_progress = False)
|
||||
|
||||
ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery)
|
||||
img2img_paste_fields = [
|
||||
|
|
@ -254,8 +254,13 @@ def create_ui():
|
|||
(seed, "Seed"),
|
||||
(subseed, "Variation seed"),
|
||||
(subseed_strength, "Variation strength"),
|
||||
# guidance
|
||||
(guidance_name, "Guidance"),
|
||||
(guidance_scale, "Guidance scale"),
|
||||
(guidance_rescale, "Guidance rescale"),
|
||||
(guidance_start, "Guidance start"),
|
||||
(guidance_stop, "Guidance stop"),
|
||||
# advanced
|
||||
(cfg_scale, "Guidance scale"),
|
||||
(cfg_scale, "CFG scale"),
|
||||
(cfg_end, "CFG end"),
|
||||
(image_cfg_scale, "Image CFG scale"),
|
||||
|
|
|
|||
|
|
@ -146,21 +146,6 @@ def create_video_inputs(tab:str, show_always:bool=False):
|
|||
return video_type, video_duration, video_loop, video_pad, video_interpolate
|
||||
|
||||
|
||||
def create_guidance_inputs(tab):
|
||||
with gr.Accordion(open=False, label="Guidance", elem_id=f"{tab}_guidance", elem_classes=["small-accordion"]):
|
||||
with gr.Group():
|
||||
with gr.Row(elem_id=f"{tab}_cfg_row", elem_classes=['flexbox']):
|
||||
cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_cfg_scale")
|
||||
cfg_end = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance end', value=1.0, elem_id=f"{tab}_cfg_end")
|
||||
with gr.Row():
|
||||
image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Refine guidance', value=6.0, elem_id=f"{tab}_image_cfg_scale")
|
||||
diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Rescale guidance', value=0.0, elem_id=f"{tab}_image_cfg_rescale")
|
||||
with gr.Row():
|
||||
diffusers_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='Attention guidance', value=0.0, elem_id=f"{tab}_pag_scale")
|
||||
diffusers_pag_adaptive = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Adaptive scaling', value=0.5, elem_id=f"{tab}_pag_adaptive")
|
||||
return cfg_scale, image_cfg_scale, diffusers_guidance_rescale, diffusers_pag_scale, diffusers_pag_adaptive, cfg_end
|
||||
|
||||
|
||||
def create_advanced_inputs(tab):
|
||||
with gr.Accordion(open=False, label="Advanced", elem_id=f"{tab}_advanced", elem_classes=["small-accordion"]):
|
||||
with gr.Group():
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
import gradio as gr
|
||||
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
|
||||
from modules import timer, shared, ui_common, ui_sections, generation_parameters_copypaste, processing_vae, images
|
||||
from modules.ui_components import ToolButton # pylint: disable=unused-import
|
||||
from modules import timer, shared, call_queue, generation_parameters_copypaste, processing_vae, images
|
||||
from modules import ui_common, ui_sections, ui_guidance
|
||||
|
||||
|
||||
def create_ui():
|
||||
|
|
@ -33,7 +32,7 @@ def create_ui():
|
|||
with gr.Accordion(open=False, label="Samplers", elem_classes=["small-accordion"], elem_id="txt2img_sampler_group"):
|
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ui_sections.create_sampler_options('txt2img')
|
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seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = ui_sections.create_seed_inputs('txt2img')
|
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('txt2img')
|
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guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('txt2img')
|
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vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('txt2img')
|
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hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('txt2img')
|
||||
enable_hr, hr_sampler_index, denoising_strength, hr_resize_mode, hr_resize_context, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative = ui_sections.create_hires_inputs('txt2img')
|
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|
|
@ -57,6 +56,7 @@ def create_ui():
|
|||
vae_type, tiling, hidiffusion,
|
||||
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
|
||||
batch_count, batch_size,
|
||||
guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
|
||||
cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
|
||||
clip_skip,
|
||||
seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
|
||||
|
|
@ -68,7 +68,7 @@ def create_ui():
|
|||
override_settings,
|
||||
]
|
||||
txt2img_dict = dict(
|
||||
fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', ''], name='Text'),
|
||||
fn=call_queue.wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', ''], name='Text'),
|
||||
_js="submit_txt2img",
|
||||
inputs=txt2img_args + txt2img_script_inputs,
|
||||
outputs=[
|
||||
|
|
@ -106,8 +106,13 @@ def create_ui():
|
|||
(seed, "Seed"),
|
||||
(subseed, "Variation seed"),
|
||||
(subseed_strength, "Variation strength"),
|
||||
# guidance
|
||||
(guidance_name, "Guidance"),
|
||||
(guidance_scale, "Guidance scale"),
|
||||
(guidance_rescale, "Guidance rescale"),
|
||||
(guidance_start, "Guidance start"),
|
||||
(guidance_stop, "Guidance stop"),
|
||||
# advanced
|
||||
(cfg_scale, "Guidance scale"),
|
||||
(cfg_scale, "CFG scale"),
|
||||
(cfg_end, "CFG end"),
|
||||
(clip_skip, "Clip skip"),
|
||||
|
|
@ -156,7 +161,7 @@ def create_ui():
|
|||
txt2img_bindings = generation_parameters_copypaste.ParamBinding(paste_button=txt2img_paste, tabname="txt2img", source_text_component=txt2img_prompt, source_image_component=None)
|
||||
generation_parameters_copypaste.register_paste_params_button(txt2img_bindings)
|
||||
|
||||
txt2img_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_prompt], outputs=[txt2img_token_counter], show_progress = False)
|
||||
txt2img_negative_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_negative_prompt], outputs=[txt2img_negative_token_counter], show_progress = False)
|
||||
txt2img_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_prompt], outputs=[txt2img_token_counter], show_progress = False)
|
||||
txt2img_negative_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_negative_prompt], outputs=[txt2img_negative_token_counter], show_progress = False)
|
||||
|
||||
ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ from scripts.xyz.xyz_grid_shared import ( # pylint: disable=no-name-in-module, u
|
|||
apply_lora,
|
||||
apply_lora_strength,
|
||||
apply_te,
|
||||
apply_guidance,
|
||||
apply_styles,
|
||||
apply_upscaler,
|
||||
apply_context,
|
||||
|
|
@ -223,6 +224,7 @@ axis_options = [
|
|||
AxisOption("[Sampler] Shift", float, apply_setting("schedulers_shift")),
|
||||
AxisOption("[Sampler] eta delta", float, apply_setting("eta_noise_seed_delta")),
|
||||
AxisOption("[Sampler] eta multiplier", float, apply_setting("scheduler_eta")),
|
||||
AxisOption("[Guidance] Guidance name", str, apply_guidance, choices=lambda: ['Default', 'CFG', 'Auto', 'Zero', 'PAG', 'APG', 'SLG', 'SEG', 'TCFG', 'FDG']),
|
||||
AxisOption("[Refine] Upscaler", str, apply_field("hr_upscaler"), cost=0.3, choices=lambda: [x.name for x in shared.sd_upscalers]),
|
||||
AxisOption("[Refine] Sampler", str, apply_hr_sampler_name, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
|
||||
AxisOption("[Refine] Denoising strength", float, apply_field("denoising_strength")),
|
||||
|
|
|
|||
|
|
@ -254,6 +254,13 @@ def apply_te(p, x, xs):
|
|||
shared.log.debug(f'XYZ grid apply text-encoder: "{x}"')
|
||||
|
||||
|
||||
def apply_guidance(p, x, xs):
|
||||
from modules.modular_guiders import guiders
|
||||
guiders = list(guiders.keys())
|
||||
p.guidance_name = [g for g in guiders if g.lower().startswith(x.lower())][0]
|
||||
shared.log.debug(f'XYZ grid apply guidance: "{p.guidance_name}"')
|
||||
|
||||
|
||||
def apply_styles(p: processing.StableDiffusionProcessingTxt2Img, x: str, _):
|
||||
p.styles.extend(x.split(','))
|
||||
shared.log.debug(f'XYZ grid apply style: "{x}"')
|
||||
|
|
|
|||
|
|
@ -324,6 +324,7 @@ class Script(scripts_manager.Script):
|
|||
|
||||
def cell(x, y, z, ix, iy, iz):
|
||||
if shared.state.interrupted:
|
||||
shared.log.warning('XYZ grid: Interrupted')
|
||||
return processing.Processed(p, [], p.seed, ""), 0
|
||||
p.xyz = True
|
||||
pc = copy(p)
|
||||
|
|
|
|||
Loading…
Reference in New Issue