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cleanup/refactor state history

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-09-12 16:12:43 -04:00
parent a8b850adf4
commit 175e9cbe29
41 changed files with 172 additions and 171 deletions
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modules/processing_diffusers.py
+10 -7
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@@ -118,7 +118,7 @@ def process_post(p: processing.StableDiffusionProcessing):
def process_base(p: processing.StableDiffusionProcessing):
shared.state.begin('Base')
jobid = shared.state.begin('Base')
txt2img = is_txt2img()
use_refiner_start = is_refiner_enabled(p) and (not p.is_hr_pass)
use_denoise_start = not txt2img and p.refiner_start > 0 and p.refiner_start < 1
@@ -164,7 +164,9 @@ def process_base(p: processing.StableDiffusionProcessing):
base_args['gate_step'] = p.gate_step
output = shared.sd_model.tgate(**base_args) # pylint: disable=not-callable
else:
taskid = shared.state.begin('Model')
output = shared.sd_model(**base_args)
shared.state.end(taskid)
if isinstance(output, dict):
output = SimpleNamespace(**output)
if isinstance(output, list):
@@ -207,8 +209,8 @@ def process_base(p: processing.StableDiffusionProcessing):
finally:
process_post(p)
shared.state.end(jobid)
shared.state.nextjob()
shared.state.end()
return output
@@ -217,6 +219,7 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
if (output is None) or (output.images is None):
return output
if p.enable_hr:
jobid = shared.state.begin('Hires')
p.is_hr_pass = True
if hasattr(p, 'init_hr'):
p.init_hr(p.hr_scale, p.hr_upscaler, force=p.hr_force)
@@ -228,7 +231,6 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
p.hr_resize_context = p.resize_context
p.hr_upscale_to_x = p.width * p.hr_scale if p.hr_resize_x == 0 else p.hr_resize_x
p.hr_upscale_to_y = p.height * p.hr_scale if p.hr_resize_y == 0 else p.hr_resize_y
prev_job = shared.state.job
# hires runs on original pipeline
if hasattr(shared.sd_model, 'restore_pipeline') and (shared.sd_model.restore_pipeline is not None) and (not shared.opts.control_hires):
@@ -240,7 +242,6 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
p.ops.append('upscale')
if shared.opts.samples_save and not p.do_not_save_samples and shared.opts.save_images_before_highres_fix and hasattr(shared.sd_model, 'vae'):
save_intermediate(p, latents=output.images, suffix="-before-hires")
shared.state.update('Upscale', 0, 1)
output.images = resize_hires(p, latents=output.images)
sd_hijack_hypertile.hypertile_set(p, hr=True)
elif torch.is_tensor(output.images) and output.images.shape[-1] == 3: # nhwc
@@ -295,7 +296,9 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
try:
if 'base' in p.skip:
extra_networks.activate(p)
taskid = shared.state.begin('Model')
output = shared.sd_model(**hires_args) # pylint: disable=not-callable
shared.state.end(taskid)
if isinstance(output, dict):
output = SimpleNamespace(**output)
if hasattr(output, 'images'):
@@ -314,7 +317,7 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
if orig_image is not None:
p.task_args['image'] = orig_image
p.denoising_strength = orig_denoise
shared.state.job = prev_job
shared.state.end(jobid)
shared.state.nextjob()
p.is_hr_pass = False
timer.process.record('hires')
@@ -326,7 +329,6 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
if (output is None) or (output.images is None):
return output
if is_refiner_enabled(p):
prev_job = shared.state.job
if shared.opts.samples_save and not p.do_not_save_samples and shared.opts.save_images_before_refiner and hasattr(shared.sd_model, 'vae'):
save_intermediate(p, latents=output.images, suffix="-before-refiner")
if shared.opts.diffusers_move_base:
@@ -335,6 +337,7 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
if shared.state.interrupted or shared.state.skipped:
shared.sd_model = orig_pipeline
return output
jobid = shared.state.begin('Refine')
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
if shared.opts.diffusers_move_refiner:
sd_models.move_model(shared.sd_refiner, devices.device)
@@ -400,7 +403,7 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
elif shared.opts.diffusers_move_refiner:
shared.log.debug('Moving to CPU: model=refiner')
sd_models.move_model(shared.sd_refiner, devices.cpu)
shared.state.job = prev_job
shared.state.end(jobid)
shared.state.nextjob()
p.is_refiner_pass = False
timer.process.record('refine')