keep previous processed state

Signed-off-by: Vladimir Mandic <mandic00@live.com>

modules/face/__init__.py

@@ -134,7 +134,7 @@ class Script(scripts_manager.Script):
             app = get_app('buffalo_l')
             from modules.face.faceid import face_id
             processed_images = face_id(p, app=app, source_images=input_images, model=ip_model, override=ip_override, cache=ip_cache, scale=ip_strength, structure=ip_structure) # run faceid pipeline
-            processed = processing.Processed(p, images_list=processed_images, seed=p.seed, subseed=p.subseed, index_of_first_image=0) # manually created processed object
+            processed = processing.get_processed(p, images_list=processed_images, seed=p.seed, subseed=p.subseed, index_of_first_image=0) # manually created processed object
         elif mode == 'PhotoMaker': # photomaker creates pipeline and triggers original process_images
             from modules.face.insightface import get_app
             app = get_app('buffalo_l')

modules/img2img.py

@@ -317,7 +317,7 @@ def img2img(id_task: str, state: str, mode: int,
     p.is_batch = mode == 5
     if p.is_batch:
         process_batch(p, img2img_batch_files, img2img_batch_input_dir, img2img_batch_output_dir, img2img_batch_inpaint_mask_dir, args)
-        processed = processing.Processed(p, [], p.seed, "")
+        processed = processing.get_processed(p, [], p.seed, "")
     else:
         processed = scripts_manager.scripts_img2img.run(p, *args)
         if processed is None:

modules/processing.py

@@ -27,6 +27,7 @@ get_sampler_index = processing_helpers.get_sampler_index
 validate_sample = processing_helpers.validate_sample
 decode_first_stage = processing_helpers.decode_first_stage
 images_tensor_to_samples = processing_helpers.images_tensor_to_samples
+processed = None # last known processed results
 
 
 class Processed:
@@ -113,6 +114,12 @@ class Processed:
         return f'{self.__class__.__name__}: {self.__dict__}'
 
 
+def get_processed(*args, **kwargs):
+    global processed # pylint: disable=global-statement
+    processed = Processed(*args, **kwargs)
+    return processed
+
+
 def process_images(p: StableDiffusionProcessing) -> Processed:
     timer.process.reset()
     debug(f'Process images: {vars(p)}')
@@ -133,7 +140,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             p.override_settings.pop(k, None)
     for k in p.override_settings.keys():
         stored_opts[k] = shared.opts.data.get(k, None) or shared.opts.data_labels[k].default
-    processed = None
+    results = None
     try:
         # if no checkpoint override or the override checkpoint can't be found, remove override entry and load opts checkpoint
         if p.override_settings.get('sd_model_checkpoint', None) is not None and sd_checkpoint.checkpoint_aliases.get(p.override_settings.get('sd_model_checkpoint')) is None:
@@ -196,11 +203,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                     shared.log.debug(f'Torch profile: {profile_args}')
                     shared.profiler = torch.profiler.profile(**profile_args)
                 shared.profiler.start()
-                processed = process_images_inner(p)
+                results = process_images_inner(p)
                 errors.profile_torch(shared.profiler, 'Process')
         else:
             with context_hypertile_vae(p), context_hypertile_unet(p):
-                processed = process_images_inner(p)
+                results = process_images_inner(p)
 
     finally:
         script_callbacks.after_process_callback(p)
@@ -215,7 +222,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 if k == 'sd_vae':
                     sd_vae.reload_vae_weights()
         timer.process.record('post')
-    return processed
+    return results
 
 
 def process_init(p: StableDiffusionProcessing):
@@ -399,10 +406,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             samples = None
             timer.process.record('init')
             if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
-                processed = p.scripts.process_images(p)
-                if processed is not None:
-                    samples = processed.images
-                    for script_image, script_infotext in zip(processed.images, processed.infotexts):
+                results = p.scripts.process_images(p)
+                if results is not None:
+                    samples = results.images
+                    for script_image, script_infotext in zip(results.images, results.infotexts):
                         output_images.append(script_image)
                         infotexts.append(script_infotext)
             if samples is None:
@@ -453,7 +460,7 @@ 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) # main save grid
 
-    processed = Processed(
+    results = Processed(
         p,
         images_list=output_images,
         seed=p.all_seeds[0],
@@ -464,7 +471,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         infotexts=infotexts,
     )
     if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner) and not (shared.state.interrupted or shared.state.skipped):
-        p.scripts.postprocess(p, processed)
+        p.scripts.postprocess(p, results)
     timer.process.record('post')
     p.ops = list(set(p.ops))
     if not p.disable_extra_networks:
@@ -474,4 +481,4 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
         devices.torch_gc(force=True, reason='final')
-    return processed
+    return results

modules/sdnq/common.py

@@ -2,7 +2,7 @@
 
 import os
 import torch
-from modules import devices, shared
+from modules import shared
 
 torch_version = float(torch.__version__[:3])
 

modules/sdnq/layers/linear/linear_int8.py

@@ -1,7 +1,6 @@
 # pylint: disable=relative-beyond-top-level,redefined-builtin,protected-access
 
-from typing import Tuple, Optional
-
+from typing import Tuple
 import torch
 
 from ...common import use_torch_compile # noqa: TID252

scripts/cogvideo.py

@@ -205,7 +205,7 @@ class Script(scripts_manager.Script):
         self.offload(offload)
         frames = self.generate(p, model)
         devices.torch_gc()
-        processed = processing.Processed(p, images_list=frames)
+        processed = processing.get_processed(p, images_list=frames)
         shared.state.end()
         return processed
 

scripts/consistory_ext.py

@@ -210,7 +210,7 @@ class Script(scripts_manager.Script):
                 images.append(image)
 
         shared.sd_model.disable_freeu()
-        processed = processing.Processed(p, images)
+        processed = processing.get_processed(p, images)
         return processed
 
     def after(self, p: processing.StableDiffusionProcessing, processed: processing.Processed, *args): # pylint: disable=arguments-differ, unused-argument

scripts/custom_code.py

@@ -2,7 +2,7 @@ import copy
 import ast
 import gradio as gr
 from modules import scripts_manager
-from modules.processing import Processed
+from modules.processing import Processed, get_processed
 from modules.shared import opts, cmd_opts, state # pylint: disable=unused-import
 
 
@@ -87,4 +87,4 @@ __webuitemp__()"""
         if isinstance(result, Processed):
             return result
 
-        return Processed(p, *display_result_data)
+        return get_processed(p, *display_result_data)

scripts/hdr.py

@@ -4,7 +4,7 @@ import numpy as np
 import gradio as gr
 from PIL import Image
 from modules import images, processing, shared, scripts_manager
-from modules.processing import Processed
+from modules.processing import get_processed
 from modules.shared import opts, state
 
 
@@ -95,5 +95,5 @@ class Script(scripts_manager.Script):
             grid = [images.image_grid(imgs, rows=1)] if opts.return_grid else []
             imgs = [img] + grid
 
-        processed = Processed(p, images_list=imgs, seed=p.seed, info=info)
+        processed = get_processed(p, images_list=imgs, seed=p.seed, info=info)
         return processed

scripts/ipinstruct.py

@@ -101,7 +101,7 @@ class Script(scripts_manager.Script):
             auto_scale = False,
             simple_cfg_mode = False,
         )
-        processed = processing.Processed(p, images_list=image_list, seed=p.seed, subseed=p.subseed, index_of_first_image=0) # manually created processed object
+        processed = processing.get_processed(p, images_list=image_list, seed=p.seed, subseed=p.subseed, index_of_first_image=0) # manually created processed object
         # p.extra_generation_params["IPInstruct"] = f''
         return processed
 

scripts/lbm_ext.py

@@ -131,6 +131,6 @@ class Script(scripts_manager.Script):
 
         if output_image is not None:
             output_image.resize((ori_h_bg, ori_w_bg))
-            return processing.Processed(p, [output_image])
+            return processing.get_processed(p, [output_image])
         else:
             return processing.Processed(p, [])

scripts/outpainting_mk_2.py

@@ -3,7 +3,7 @@ import numpy as np
 import gradio as gr
 from PIL import Image, ImageDraw
 from modules import images, scripts_manager
-from modules.processing import Processed, process_images
+from modules.processing import get_processed, process_images
 from modules.shared import opts, state
 
 
@@ -222,7 +222,7 @@ class Script(scripts_manager.Script):
         combined_grid_image = images.image_grid(all_processed_images)
         if opts.return_grid and len(all_processed_images) > 1:
             all_images = [combined_grid_image] + all_processed_images
-        res = Processed(p, all_images, initial_seed_and_info[0], initial_seed_and_info[1])
+        res = get_processed(p, all_images, initial_seed_and_info[0], initial_seed_and_info[1])
         if opts.samples_save:
             for img in all_processed_images:
                 images.save_image(img, p.outpath_samples, "", res.seed, p.prompt, opts.samples_format, info=res.info, p=p)

scripts/poor_mans_outpainting.py

@@ -2,7 +2,7 @@ import math
 import gradio as gr
 from PIL import Image, ImageDraw
 from modules import images, devices, scripts_manager
-from modules.processing import Processed, process_images
+from modules.processing import get_processed, process_images
 from modules.shared import opts, state, log
 
 
@@ -108,5 +108,5 @@ class Script(scripts_manager.Script):
         combined_image = images.combine_grid(grid)
         if opts.samples_save:
             images.save_image(combined_image, p.outpath_samples, "", initial_seed, p.prompt, opts.samples_format, info=initial_info, p=p)
-        processed = Processed(p, [combined_image], initial_seed, initial_info)
+        processed = get_processed(p, [combined_image], initial_seed, initial_info)
         return processed

scripts/prompts_from_file.py

@@ -3,7 +3,7 @@ import random
 import shlex
 import gradio as gr
 from modules import sd_samplers, errors, scripts_manager
-from modules.processing import Processed, process_images
+from modules.processing import get_processed, process_images
 from modules.shared import state, log
 
 
@@ -148,4 +148,4 @@ class Script(scripts_manager.Script):
             all_negative += proc.all_negative_prompts
             images += proc.images
             infotexts += proc.infotexts
-        return Processed(p, images, p.seed, "", all_prompts=all_prompts, all_seeds=all_seeds, all_negative_prompts=all_negative, infotexts=infotexts)
+        return get_processed(p, images, p.seed, "", all_prompts=all_prompts, all_seeds=all_seeds, all_negative_prompts=all_negative, infotexts=infotexts)

scripts/pulid_ext.py

@@ -273,7 +273,7 @@ class Script(scripts_manager.Script):
                     id_scale=strength,
                     )[0]
             info = processing.create_infotext(p)
-            processed = processing.Processed(p, [output], info=info)
+            processed = processing.get_processed(p, [output], info=info)
             shared.state.end()
         else: # let processing run the pipeline
             p.task_args['id_embedding'] = id_embedding

scripts/sd_upscale.py

@@ -2,7 +2,7 @@ import math
 import gradio as gr
 from PIL import Image
 from modules import processing, shared, images, devices, scripts_manager
-from modules.processing import Processed
+from modules.processing import get_processed
 from modules.shared import opts, state, log
 
 
@@ -89,6 +89,6 @@ class Script(scripts_manager.Script):
             if opts.samples_save:
                 images.save_image(combined_image, p.outpath_samples, "", start_seed, p.prompt, opts.samples_format, info=initial_info, p=p)
 
-        processed = Processed(p, result_images, seed, initial_info)
+        processed = get_processed(p, result_images, seed, initial_info)
         log.info(f"SD upscale: images={result_images}")
         return processed