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merge: modules/processing_info.py

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vladmandic
2026-03-13 14:30:53 +01:00
parent 928448b654
commit 4effd92663
1 changed files with 38 additions and 21 deletions
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modules/processing_info.py
+38 -21
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@@ -62,7 +62,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
"Styles": "; ".join(p.styles) if p.styles is not None and len(p.styles) > 0 else None,
"App": 'SD.Next',
"Version": git_commit,
"Parser": shared.opts.prompt_attention if shared.opts.prompt_attention != 'native' else None,
"Parser": (getattr(p, 'prompt_attention', None) or shared.opts.prompt_attention) if (getattr(p, 'prompt_attention', None) or shared.opts.prompt_attention) != 'native' else None,
"Comment": comment,
"Pipeline": shared.sd_model.__class__.__name__,
"TE": None if (shared.opts.sd_text_encoder is None or shared.opts.sd_text_encoder == 'Default') else shared.opts.sd_text_encoder,
@@ -146,7 +146,13 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
args['Resize name mask'] = p.resize_name_mask
args['Resize scale mask'] = float(p.scale_by_mask)
if 'detailer' in p.ops:
args["Detailer"] = ', '.join(shared.opts.detailer_models) if len(shared.opts.detailer_args) == 0 else shared.opts.detailer_args
_d_models = getattr(p, 'detailer_models', None)
if _d_models is not None and len(_d_models) > 0:
args["Detailer"] = ', '.join(_d_models)
elif len(shared.opts.detailer_args) > 0:
args["Detailer"] = shared.opts.detailer_args
else:
args["Detailer"] = ', '.join(shared.opts.detailer_models)
args["Detailer steps"] = p.detailer_steps
args["Detailer strength"] = p.detailer_strength
args["Detailer resolution"] = p.detailer_resolution if p.detailer_resolution != 1024 else None
@@ -154,31 +160,42 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
args["Detailer negative"] = p.detailer_negative if len(p.detailer_negative) > 0 else None
if 'color' in p.ops:
args["Color correction"] = True
if shared.opts.token_merging_method == 'ToMe': # tome/todo
args['ToMe'] = shared.opts.tome_ratio if shared.opts.tome_ratio != 0 else None
elif shared.opts.token_merging_method == 'ToDo':
args['ToDo'] = shared.opts.todo_ratio if shared.opts.todo_ratio != 0 else None
def _p_or_opt(key):
val = getattr(p, key, None)
if val is not None:
return val
return getattr(shared.opts, key, None)
_token_method = _p_or_opt('token_merging_method')
_tome = _p_or_opt('tome_ratio')
_todo = _p_or_opt('todo_ratio')
if _token_method == 'ToMe': # tome/todo
args['ToMe'] = _tome if _tome != 0 else None
elif _token_method == 'ToDo':
args['ToDo'] = _todo if _todo != 0 else None
if hasattr(shared.sd_model, 'embedding_db') and len(shared.sd_model.embedding_db.embeddings_used) > 0: # register used embeddings
args['Embeddings'] = ', '.join(shared.sd_model.embedding_db.embeddings_used)
# samplers
if getattr(p, 'sampler_name', None) is not None and p.sampler_name.lower() != 'default':
args["Sampler eta delta"] = shared.opts.eta_noise_seed_delta if shared.opts.eta_noise_seed_delta != 0 and sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p) else None
_eta_delta = _p_or_opt('eta_noise_seed_delta')
args["Sampler eta delta"] = _eta_delta if _eta_delta != 0 and sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p) else None
args["Sampler eta multiplier"] = p.initial_noise_multiplier if getattr(p, 'initial_noise_multiplier', 1.0) != 1.0 else None
args['Sampler timesteps'] = shared.opts.schedulers_timesteps if shared.opts.schedulers_timesteps != shared.opts.data_labels.get('schedulers_timesteps').default else None
args['Sampler spacing'] = shared.opts.schedulers_timestep_spacing if shared.opts.schedulers_timestep_spacing != shared.opts.data_labels.get('schedulers_timestep_spacing').default else None
args['Sampler sigma'] = shared.opts.schedulers_sigma if shared.opts.schedulers_sigma != shared.opts.data_labels.get('schedulers_sigma').default else None
args['Sampler order'] = shared.opts.schedulers_solver_order if shared.opts.schedulers_solver_order != shared.opts.data_labels.get('schedulers_solver_order').default else None
args['Sampler type'] = shared.opts.schedulers_prediction_type if shared.opts.schedulers_prediction_type != shared.opts.data_labels.get('schedulers_prediction_type').default else None
args['Sampler beta schedule'] = shared.opts.schedulers_beta_schedule if shared.opts.schedulers_beta_schedule != shared.opts.data_labels.get('schedulers_beta_schedule').default else None
args['Sampler low order'] = shared.opts.schedulers_use_loworder if shared.opts.schedulers_use_loworder != shared.opts.data_labels.get('schedulers_use_loworder').default else None
args['Sampler dynamic'] = shared.opts.schedulers_use_thresholding if shared.opts.schedulers_use_thresholding != shared.opts.data_labels.get('schedulers_use_thresholding').default else None
args['Sampler rescale'] = shared.opts.schedulers_rescale_betas if shared.opts.schedulers_rescale_betas != shared.opts.data_labels.get('schedulers_rescale_betas').default else None
args['Sampler beta start'] = shared.opts.schedulers_beta_start if shared.opts.schedulers_beta_start != shared.opts.data_labels.get('schedulers_beta_start').default else None
args['Sampler beta end'] = shared.opts.schedulers_beta_end if shared.opts.schedulers_beta_end != shared.opts.data_labels.get('schedulers_beta_end').default else None
args['Sampler range'] = shared.opts.schedulers_timesteps_range if shared.opts.schedulers_timesteps_range != shared.opts.data_labels.get('schedulers_timesteps_range').default else None
args['Sampler shift'] = shared.opts.schedulers_shift if shared.opts.schedulers_shift != shared.opts.data_labels.get('schedulers_shift').default else None
args['Sampler dynamic shift'] = shared.opts.schedulers_dynamic_shift if shared.opts.schedulers_dynamic_shift != shared.opts.data_labels.get('schedulers_dynamic_shift').default else None
args['Sampler timesteps'] = _p_or_opt('schedulers_timesteps') if _p_or_opt('schedulers_timesteps') != shared.opts.data_labels.get('schedulers_timesteps').default else None
args['Sampler spacing'] = _p_or_opt('schedulers_timestep_spacing') if _p_or_opt('schedulers_timestep_spacing') != shared.opts.data_labels.get('schedulers_timestep_spacing').default else None
args['Sampler sigma'] = _p_or_opt('schedulers_sigma') if _p_or_opt('schedulers_sigma') != shared.opts.data_labels.get('schedulers_sigma').default else None
args['Sampler order'] = _p_or_opt('schedulers_solver_order') if _p_or_opt('schedulers_solver_order') != shared.opts.data_labels.get('schedulers_solver_order').default else None
args['Sampler type'] = _p_or_opt('schedulers_prediction_type') if _p_or_opt('schedulers_prediction_type') != shared.opts.data_labels.get('schedulers_prediction_type').default else None
args['Sampler beta schedule'] = _p_or_opt('schedulers_beta_schedule') if _p_or_opt('schedulers_beta_schedule') != shared.opts.data_labels.get('schedulers_beta_schedule').default else None
args['Sampler low order'] = _p_or_opt('schedulers_use_loworder') if _p_or_opt('schedulers_use_loworder') != shared.opts.data_labels.get('schedulers_use_loworder').default else None
args['Sampler dynamic'] = _p_or_opt('schedulers_use_thresholding') if _p_or_opt('schedulers_use_thresholding') != shared.opts.data_labels.get('schedulers_use_thresholding').default else None
args['Sampler rescale'] = _p_or_opt('schedulers_rescale_betas') if _p_or_opt('schedulers_rescale_betas') != shared.opts.data_labels.get('schedulers_rescale_betas').default else None
args['Sampler beta start'] = _p_or_opt('schedulers_beta_start') if _p_or_opt('schedulers_beta_start') != shared.opts.data_labels.get('schedulers_beta_start').default else None
args['Sampler beta end'] = _p_or_opt('schedulers_beta_end') if _p_or_opt('schedulers_beta_end') != shared.opts.data_labels.get('schedulers_beta_end').default else None
args['Sampler range'] = _p_or_opt('schedulers_timesteps_range') if _p_or_opt('schedulers_timesteps_range') != shared.opts.data_labels.get('schedulers_timesteps_range').default else None
args['Sampler shift'] = _p_or_opt('schedulers_shift') if _p_or_opt('schedulers_shift') != shared.opts.data_labels.get('schedulers_shift').default else None
args['Sampler dynamic shift'] = _p_or_opt('schedulers_dynamic_shift') if _p_or_opt('schedulers_dynamic_shift') != shared.opts.data_labels.get('schedulers_dynamic_shift').default else None
# model specific
if shared.sd_model_type == 'h1':