nodes/mcmonkeyprojects-sd-dynamic-thresholding
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actually just fix every single casing mixup

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Alex "mcmonkey" Goodwin
2023-10-29 07:34:22 -07:00
parent 9fe47f4e7a
commit 83f619ab37
4 changed files with 55 additions and 55 deletions
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scripts/dynamic_thresholding.py
+25 -25
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@@ -39,8 +39,8 @@ class Script(scripts.Script):
return scripts.AlwaysVisible
def ui(self, is_img2img):
def vis_change(isVis):
return {"visible": isVis, "__type__": "update"}
def vis_change(is_vis):
return {"visible": is_vis, "__type__": "update"}
# "Dynamic Thresholding (CFG Scale Fix)"
dtrue = gr.Checkbox(value=True, visible=False)
dfalse = gr.Checkbox(value=False, visible=False)
@@ -64,11 +64,11 @@ class Script(scripts.Script):
separate_feature_channels = gr.Checkbox(value=True, label="Separate Feature Channels", elem_id='dynthres_separate_feature_channels')
scaling_startpoint = gr.Radio(["ZERO", "MEAN"], value="MEAN", label="Scaling Startpoint")
variability_measure = gr.Radio(["STD", "AD"], value="AD", label="Variability Measure")
def shouldShowSchedulerValue(cfgMode, mimicMode):
sched_vis = cfgMode in MODES_WITH_VALUE or mimicMode in MODES_WITH_VALUE
return vis_change(sched_vis), vis_change(mimicMode != "Constant"), vis_change(cfgMode != "Constant")
cfg_mode.change(shouldShowSchedulerValue, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
mimic_mode.change(shouldShowSchedulerValue, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
def should_show_scheduler_value(cfg_mode, mimic_mode):
sched_vis = cfg_mode in MODES_WITH_VALUE or mimic_mode in MODES_WITH_VALUE
return vis_change(sched_vis), vis_change(mimic_mode != "Constant"), vis_change(cfg_mode != "Constant")
cfg_mode.change(should_show_scheduler_value, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
mimic_mode.change(should_show_scheduler_value, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
enabled.change(
_js="dynthres_update_enabled",
fn=lambda x, y: {"visible": x, "__type__": "update"},
@@ -143,19 +143,19 @@ class Script(scripts.Script):
# Make a placeholder sampler
sampler = sd_samplers.all_samplers_map[orig_sampler_name]
dtData = dynthres_core.DynThresh(mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, experiment_mode, p.steps, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi)
dt_data = dynthres_core.DynThresh(mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, experiment_mode, p.steps, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi)
if orig_sampler_name == "UniPC":
def uniPCConstructor(model):
return CustomVanillaSDSampler(dynthres_unipc.CustomUniPCSampler, model, dtData)
newSampler = sd_samplers_common.SamplerData(fixed_sampler_name, uniPCConstructor, sampler.aliases, sampler.options)
def unipc_constructor(model):
return CustomVanillaSDSampler(dynthres_unipc.CustomUniPCSampler, model, dt_data)
new_sampler = sd_samplers_common.SamplerData(fixed_sampler_name, unipc_constructor, sampler.aliases, sampler.options)
else:
def newConstructor(model):
def new_constructor(model):
result = sampler.constructor(model)
cfg = CustomCFGDenoiser(result if IS_AUTO_16 else result.model_wrap_cfg.inner_model, dtData)
cfg = CustomCFGDenoiser(result if IS_AUTO_16 else result.model_wrap_cfg.inner_model, dt_data)
result.model_wrap_cfg = cfg
return result
newSampler = sd_samplers_common.SamplerData(fixed_sampler_name, newConstructor, sampler.aliases, sampler.options)
return fixed_sampler_name, newSampler
new_sampler = sd_samplers_common.SamplerData(fixed_sampler_name, new_constructor, sampler.aliases, sampler.options)
return fixed_sampler_name, new_sampler
# Apply for usage
p.orig_sampler_name = orig_sampler_name
@@ -163,14 +163,14 @@ class Script(scripts.Script):
p.fixed_samplers = []
if orig_latent_sampler_name:
latent_sampler_name, latentSampler = make_sampler(orig_latent_sampler_name)
sd_samplers.all_samplers_map[latent_sampler_name] = latentSampler
latent_sampler_name, latent_sampler = make_sampler(orig_latent_sampler_name)
sd_samplers.all_samplers_map[latent_sampler_name] = latent_sampler
p.fixed_samplers.append(latent_sampler_name)
p.latent_sampler = latent_sampler_name
if orig_sampler_name != orig_latent_sampler_name:
p.sampler_name, newSampler = make_sampler(orig_sampler_name)
sd_samplers.all_samplers_map[p.sampler_name] = newSampler
p.sampler_name, new_sampler = make_sampler(orig_sampler_name)
sd_samplers.all_samplers_map[p.sampler_name] = new_sampler
p.fixed_samplers.append(p.sampler_name)
else:
p.sampler_name = p.latent_sampler
@@ -193,16 +193,16 @@ class Script(scripts.Script):
######################### CompVis Implementation logic #########################
class CustomVanillaSDSampler(sd_samplers_compvis.VanillaStableDiffusionSampler):
def __init__(self, constructor, sd_model, dtData):
def __init__(self, constructor, sd_model, dt_data):
super().__init__(constructor, sd_model)
self.sampler.main_class = dtData
self.sampler.main_class = dt_data
######################### K-Diffusion Implementation logic #########################
class CustomCFGDenoiser(cfgdenoisekdiff):
def __init__(self, model, dtData):
def __init__(self, model, dt_data):
super().__init__(model)
self.main_class = dtData
self.main_class = dt_data
def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
if isinstance(uncond, dict) and 'crossattn' in uncond:
@@ -258,11 +258,11 @@ def make_axis_options():
if not any("[DynThres]" in x.label for x in xyz_grid.axis_options):
xyz_grid.axis_options.extend(extra_axis_options)
def callbackBeforeUi():
def callback_before_ui():
try:
make_axis_options()
except Exception as e:
traceback.print_exc()
print(f"Failed to add support for X/Y/Z Plot Script because: {e}")
script_callbacks.on_before_ui(callbackBeforeUi)
script_callbacks.on_before_ui(callback_before_ui)