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lora refactor in progress

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2024-11-30 12:29:58 -05:00
parent 6ec93f2d46
commit eee85e5a4e
7 changed files with 109 additions and 95 deletions
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modules/processing_diffusers.py
+12 -9
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@@ -199,11 +199,6 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
if hasattr(shared.sd_model, "vae") and output.images is not None and len(output.images) > 0:
output.images = processing_vae.vae_decode(latents=output.images, model=shared.sd_model, full_quality=p.full_quality, output_type='pil', width=p.hr_upscale_to_x, height=p.hr_upscale_to_y) # controlnet cannnot deal with latent input
p.task_args['image'] = output.images # replace so hires uses new output
sd_models.move_model(shared.sd_model, devices.device)
if hasattr(shared.sd_model, 'unet'):
sd_models.move_model(shared.sd_model.unet, devices.device)
if hasattr(shared.sd_model, 'transformer'):
sd_models.move_model(shared.sd_model.transformer, devices.device)
update_sampler(p, shared.sd_model, second_pass=True)
orig_denoise = p.denoising_strength
p.denoising_strength = strength
@@ -227,6 +222,11 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
shared.state.job = 'HiRes'
shared.state.sampling_steps = hires_args.get('prior_num_inference_steps', None) or p.steps or hires_args.get('num_inference_steps', None)
try:
sd_models.move_model(shared.sd_model, devices.device)
if hasattr(shared.sd_model, 'unet'):
sd_models.move_model(shared.sd_model.unet, devices.device)
if hasattr(shared.sd_model, 'transformer'):
sd_models.move_model(shared.sd_model.transformer, devices.device)
sd_models_compile.check_deepcache(enable=True)
output = shared.sd_model(**hires_args) # pylint: disable=not-callable
if isinstance(output, dict):
@@ -405,6 +405,9 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.sd_model = orig_pipeline
return results
if shared.opts.diffusers_offload_mode == "balanced":
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
# sanitize init_images
if hasattr(p, 'init_images') and getattr(p, 'init_images', None) is None:
del p.init_images
@@ -427,10 +430,6 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
if p.negative_prompts is None or len(p.negative_prompts) == 0:
p.negative_prompts = p.all_negative_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size]
# load loras
networks.network_load()
sd_models.move_model(shared.sd_model, devices.device)
sd_models_compile.openvino_recompile_model(p, hires=False, refiner=False) # recompile if a parameter changes
if 'base' not in p.skip:
@@ -461,6 +460,10 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
timer.process.add('lora', networks.total_time())
shared.sd_model = orig_pipeline
if shared.opts.diffusers_offload_mode == "balanced":
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
if p.state == '':
global last_p # pylint: disable=global-statement
last_p = p