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mirror of https://github.com/vladmandic/automatic synced 2026-09-19 01:04:32 +02:00
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major refactor: remove backend original

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-07-05 13:16:46 -04:00
parent f408e5f315
commit e8b5ea3847
317 changed files with 386 additions and 39149 deletions
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modules/processing.py
+10 -47
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@@ -1,10 +1,9 @@
import os
import json
import time
from contextlib import nullcontext
import numpy as np
from PIL import Image, ImageOps
from modules import shared, devices, errors, images, scripts_manager, memstats, lowvram, script_callbacks, extra_networks, detailer, sd_models, sd_checkpoint, sd_vae, processing_helpers, timer, face_restoration, token_merge
from modules import shared, devices, errors, images, scripts_manager, memstats, script_callbacks, extra_networks, detailer, sd_models, sd_checkpoint, sd_vae, processing_helpers, timer, face_restoration, token_merge
from modules.sd_hijack_hypertile import context_hypertile_vae, context_hypertile_unet
from modules.processing_class import StableDiffusionProcessing, StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, StableDiffusionProcessingControl, StableDiffusionProcessingVideo # pylint: disable=unused-import
from modules.processing_info import create_infotext
@@ -20,8 +19,6 @@ create_binary_mask = processing_helpers.create_binary_mask
apply_overlay = processing_helpers.apply_overlay
apply_color_correction = processing_helpers.apply_color_correction
setup_color_correction = processing_helpers.setup_color_correction
txt2img_image_conditioning = processing_helpers.txt2img_image_conditioning
img2img_image_conditioning = processing_helpers.img2img_image_conditioning
fix_seed = processing_helpers.fix_seed
get_fixed_seed = processing_helpers.get_fixed_seed
create_random_tensors = processing_helpers.create_random_tensors
@@ -65,12 +62,6 @@ class Processed:
self.job_timestamp = shared.state.job_timestamp
self.clip_skip = p.clip_skip
self.eta = p.eta
self.ddim_discretize = p.ddim_discretize
self.s_churn = p.s_churn
self.s_tmin = p.s_tmin
self.s_tmax = p.s_tmax
self.s_noise = p.s_noise
self.s_min_uncond = p.s_min_uncond
self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0]
self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]
self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1
@@ -170,7 +161,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if 'Model' not in shared.opts.cuda_compile:
token_merge.apply_token_merging(p.sd_model)
from modules import sd_hijack_freeu, para_attention, teacache
sd_hijack_freeu.apply_freeu(p, not shared.native)
sd_hijack_freeu.apply_freeu(p)
para_attention.apply_first_block_cache()
teacache.apply_teacache(p)
@@ -207,8 +198,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
shared.log.debug(f'Torch profile: {profile_args}')
shared.profiler = torch.profiler.profile(**profile_args)
shared.profiler.start()
if not shared.native:
shared.profiler.step()
processed = process_images_inner(p)
errors.profile_torch(shared.profiler, 'Process')
else:
@@ -279,25 +268,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
else:
assert p.prompt is not None
if not shared.native:
import modules.sd_hijack # pylint: disable=redefined-outer-name
modules.sd_hijack.model_hijack.apply_circular(p.tiling)
modules.sd_hijack.model_hijack.clear_comments()
comments = {}
infotexts = []
output_images = []
process_init(p)
if not shared.native and os.path.exists(shared.opts.embeddings_dir) and not p.do_not_reload_embeddings:
modules.sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=False)
if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
p.scripts.process(p)
ema_scope_context = p.sd_model.ema_scope if not shared.native else nullcontext
if not shared.native:
shared.state.job_count = p.n_iter
shared.state.batch_count = p.n_iter
with devices.inference_context(), ema_scope_context():
with devices.inference_context():
t0 = time.time()
if not hasattr(p, 'skip_init'):
p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
@@ -316,9 +296,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
shared.log.debug(f'Process interrupted: {n+1}/{p.n_iter}')
break
if shared.native:
from modules import ipadapter
ipadapter.apply(shared.sd_model, p)
from modules import ipadapter
ipadapter.apply(shared.sd_model, p)
if not hasattr(p, 'keep_prompts'):
p.prompts = p.all_prompts[n * p.batch_size:(n+1) * p.batch_size]
p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n+1) * p.batch_size]
@@ -329,8 +308,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if len(p.prompts) == 0:
break
p.prompts, p.network_data = extra_networks.parse_prompts(p.prompts)
if not shared.native:
extra_networks.activate(p, p.network_data)
if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
@@ -342,22 +319,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
samples = processed.images
infotexts += processed.infotexts
if samples is None:
if not shared.native:
from modules.processing_original import process_original
samples = process_original(p)
elif shared.native:
from modules.processing_diffusers import process_diffusers
samples = process_diffusers(p)
else:
raise ValueError(f"Unknown backend {shared.backend}")
from modules.processing_diffusers import process_diffusers
samples = process_diffusers(p)
timer.process.record('process')
if not shared.opts.keep_incomplete and shared.state.interrupted:
samples = []
if not shared.native and (shared.cmd_opts.lowvram or shared.cmd_opts.medvram):
lowvram.send_everything_to_cpu()
devices.torch_gc()
if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
p.scripts.postprocess_batch(p, samples, batch_number=n)
if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
@@ -444,15 +412,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
timer.process.record('post')
del samples
if not shared.native:
extra_networks.deactivate(p, p.network_data)
devices.torch_gc()
if hasattr(shared.sd_model, 'restore_pipeline') and shared.sd_model.restore_pipeline is not None:
shared.sd_model.restore_pipeline()
if shared.native: # reset pipeline for each iteration
shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.TEXT_2_IMAGE)
shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.TEXT_2_IMAGE)
t1 = time.time()
@@ -471,9 +435,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if shared.opts.grid_save:
images.save_image(grid, p.outpath_grids, "", p.all_seeds[0], p.all_prompts[0], shared.opts.grid_format, info=grid_info, p=p, grid=True, suffix="-grid") # main save grid
if shared.native:
from modules import ipadapter
ipadapter.unapply(shared.sd_model, unload=getattr(p, 'ip_adapter_unload', False))
from modules import ipadapter
ipadapter.unapply(shared.sd_model, unload=getattr(p, 'ip_adapter_unload', False))
if shared.opts.include_mask:
if shared.opts.mask_apply_overlay and p.overlay_images is not None and len(p.overlay_images) > 0: