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mirror of https://github.com/vladmandic/automatic synced 2026-09-02 02:50:47 +02:00
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yet another lora refactor

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2024-12-09 13:40:19 -05:00
parent f346cccb51
commit 1185950c4a
16 changed files with 194 additions and 217 deletions
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modules/processing_diffusers.py
+9 -6
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@@ -4,7 +4,7 @@ import time
import numpy as np
import torch
import torchvision.transforms.functional as TF
from modules import shared, devices, processing, sd_models, errors, sd_hijack_hypertile, processing_vae, sd_models_compile, hidiffusion, timer, modelstats
from modules import shared, devices, processing, sd_models, errors, sd_hijack_hypertile, processing_vae, sd_models_compile, hidiffusion, timer, modelstats, extra_networks
from modules.processing_helpers import resize_hires, calculate_base_steps, calculate_hires_steps, calculate_refiner_steps, save_intermediate, update_sampler, is_txt2img, is_refiner_enabled
from modules.processing_args import set_pipeline_args
from modules.onnx_impl import preprocess_pipeline as preprocess_onnx_pipeline, check_parameters_changed as olive_check_parameters_changed
@@ -89,6 +89,7 @@ def process_base(p: processing.StableDiffusionProcessing):
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)
extra_networks.activate(p)
hidiffusion.apply(p, shared.sd_model_type)
# if 'image' in base_args:
# base_args['image'] = set_latents(p)
@@ -223,11 +224,14 @@ 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:
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
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)
if 'base' in p.skip:
extra_networks.activate(p)
sd_models_compile.check_deepcache(enable=True)
output = shared.sd_model(**hires_args) # pylint: disable=not-callable
if isinstance(output, dict):
@@ -345,6 +349,7 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
def process_decode(p: processing.StableDiffusionProcessing, output):
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
if output is not None:
if not hasattr(output, 'images') and hasattr(output, 'frames'):
shared.log.debug(f'Generated: frames={len(output.frames[0])}')
@@ -405,8 +410,6 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.sd_model = orig_pipeline
return results
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
@@ -453,13 +456,13 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.sd_model = orig_pipeline
return results
results = process_decode(p, output)
extra_networks.deactivate(p)
timer.process.add('lora', networks.timer.total)
results = process_decode(p, output)
timer.process.record('decode')
timer.process.add('lora', networks.total_time())
shared.sd_model = orig_pipeline
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
if p.state == '':