From a609bd56b4206460d1df3c3022025fc78b66718f Mon Sep 17 00:00:00 2001
From: papuSpartan <macabeg@icloud.com>
Date: Sat, 1 Apr 2023 22:18:35 -0500
Subject: Transition to using settings through UI instead of cmd line args.
 Added feature to only apply to hr-fix. Install package using
 requirements_versions.txt

---
 modules/processing.py | 35 +++++++++++++++++++++++++++++++++++
 1 file changed, 35 insertions(+)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 6d9c6a8d..e115aadd 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -29,6 +29,7 @@ from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion
 
 from einops import repeat, rearrange
 from blendmodes.blend import blendLayers, BlendType
+import tomesd
 
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
 opt_C = 4
@@ -500,9 +501,28 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
+        if opts.token_merging:
+
+            if p.hr_second_pass_steps < 1 and not opts.token_merging_hr_only:
+                tomesd.apply_patch(
+                    p.sd_model,
+                    ratio=opts.token_merging_ratio,
+                    max_downsample=opts.token_merging_maximum_down_sampling,
+                    sx=opts.token_merging_stride_x,
+                    sy=opts.token_merging_stride_y,
+                    use_rand=opts.token_merging_random,
+                    merge_attn=opts.token_merging_merge_attention,
+                    merge_crossattn=opts.token_merging_merge_cross_attention,
+                    merge_mlp=opts.token_merging_merge_mlp
+                )
+
         res = process_images_inner(p)
 
     finally:
+        # undo model optimizations made by tomesd
+        if opts.token_merging:
+            tomesd.remove_patch(p.sd_model)
+
         # restore opts to original state
         if p.override_settings_restore_afterwards:
             for k, v in stored_opts.items():
@@ -938,6 +958,21 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         x = None
         devices.torch_gc()
 
+        # apply token merging optimizations from tomesd for high-res pass
+        # check if hr_only so we don't redundantly apply patch
+        if opts.token_merging and opts.token_merging_hr_only:
+            tomesd.apply_patch(
+                self.sd_model,
+                ratio=opts.token_merging_ratio,
+                max_downsample=opts.token_merging_maximum_down_sampling,
+                sx=opts.token_merging_stride_x,
+                sy=opts.token_merging_stride_y,
+                use_rand=opts.token_merging_random,
+                merge_attn=opts.token_merging_merge_attention,
+                merge_crossattn=opts.token_merging_merge_cross_attention,
+                merge_mlp=opts.token_merging_merge_mlp
+            )
+
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
         return samples
-- 
cgit v1.2.3


From c707b7df95a61b66a05be94e805e1be9a432e294 Mon Sep 17 00:00:00 2001
From: papuSpartan <macabeg@icloud.com>
Date: Sat, 1 Apr 2023 23:47:10 -0500
Subject: remove excess condition

---
 modules/processing.py | 29 +++++++++++++++--------------
 1 file changed, 15 insertions(+), 14 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index e115aadd..55735572 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -501,26 +501,26 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
-        if opts.token_merging:
-
-            if p.hr_second_pass_steps < 1 and not opts.token_merging_hr_only:
-                tomesd.apply_patch(
-                    p.sd_model,
-                    ratio=opts.token_merging_ratio,
-                    max_downsample=opts.token_merging_maximum_down_sampling,
-                    sx=opts.token_merging_stride_x,
-                    sy=opts.token_merging_stride_y,
-                    use_rand=opts.token_merging_random,
-                    merge_attn=opts.token_merging_merge_attention,
-                    merge_crossattn=opts.token_merging_merge_cross_attention,
-                    merge_mlp=opts.token_merging_merge_mlp
-                )
+        if opts.token_merging and not opts.token_merging_hr_only:
+            print("applying token merging to all passes")
+            tomesd.apply_patch(
+                p.sd_model,
+                ratio=opts.token_merging_ratio,
+                max_downsample=opts.token_merging_maximum_down_sampling,
+                sx=opts.token_merging_stride_x,
+                sy=opts.token_merging_stride_y,
+                use_rand=opts.token_merging_random,
+                merge_attn=opts.token_merging_merge_attention,
+                merge_crossattn=opts.token_merging_merge_cross_attention,
+                merge_mlp=opts.token_merging_merge_mlp
+            )
 
         res = process_images_inner(p)
 
     finally:
         # undo model optimizations made by tomesd
         if opts.token_merging:
+            print('removing token merging model optimizations')
             tomesd.remove_patch(p.sd_model)
 
         # restore opts to original state
@@ -961,6 +961,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         # apply token merging optimizations from tomesd for high-res pass
         # check if hr_only so we don't redundantly apply patch
         if opts.token_merging and opts.token_merging_hr_only:
+            print("applying token merging for high-res pass")
             tomesd.apply_patch(
                 self.sd_model,
                 ratio=opts.token_merging_ratio,
-- 
cgit v1.2.3


From 5c8e53d5e98da0eabf384318955c57842d612c07 Mon Sep 17 00:00:00 2001
From: papuSpartan <macabeg@icloud.com>
Date: Tue, 4 Apr 2023 02:26:44 -0500
Subject: Allow different merge ratios to be used for each pass. Make toggle
 cmd flag work again. Remove ratio flag. Remove warning about controlnet being
 incompatible

---
 modules/processing.py | 44 +++++++++++++++-----------------------------
 1 file changed, 15 insertions(+), 29 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 55735572..670a7a28 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -501,26 +501,16 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
-        if opts.token_merging and not opts.token_merging_hr_only:
-            print("applying token merging to all passes")
-            tomesd.apply_patch(
-                p.sd_model,
-                ratio=opts.token_merging_ratio,
-                max_downsample=opts.token_merging_maximum_down_sampling,
-                sx=opts.token_merging_stride_x,
-                sy=opts.token_merging_stride_y,
-                use_rand=opts.token_merging_random,
-                merge_attn=opts.token_merging_merge_attention,
-                merge_crossattn=opts.token_merging_merge_cross_attention,
-                merge_mlp=opts.token_merging_merge_mlp
-            )
+        if (opts.token_merging or cmd_opts.token_merging) and not opts.token_merging_hr_only:
+            print("\nApplying token merging\n")
+            sd_models.apply_token_merging(sd_model=p.sd_model, hr=False)
 
         res = process_images_inner(p)
 
     finally:
         # undo model optimizations made by tomesd
-        if opts.token_merging:
-            print('removing token merging model optimizations')
+        if opts.token_merging or cmd_opts.token_merging:
+            print('\nRemoving token merging model optimizations\n')
             tomesd.remove_patch(p.sd_model)
 
         # restore opts to original state
@@ -959,20 +949,16 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         devices.torch_gc()
 
         # apply token merging optimizations from tomesd for high-res pass
-        # check if hr_only so we don't redundantly apply patch
-        if opts.token_merging and opts.token_merging_hr_only:
-            print("applying token merging for high-res pass")
-            tomesd.apply_patch(
-                self.sd_model,
-                ratio=opts.token_merging_ratio,
-                max_downsample=opts.token_merging_maximum_down_sampling,
-                sx=opts.token_merging_stride_x,
-                sy=opts.token_merging_stride_y,
-                use_rand=opts.token_merging_random,
-                merge_attn=opts.token_merging_merge_attention,
-                merge_crossattn=opts.token_merging_merge_cross_attention,
-                merge_mlp=opts.token_merging_merge_mlp
-            )
+        # check if hr_only so we are not redundantly patching
+        if (cmd_opts.token_merging or opts.token_merging) and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio):
+            # case where user wants to use separate merge ratios
+            if not opts.token_merging_hr_only:
+                # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive)
+                print('Temporarily reverting token merging optimizations in preparation for next pass')
+                tomesd.remove_patch(self.sd_model)
+
+            print("\nApplying token merging for high-res pass\n")
+            sd_models.apply_token_merging(sd_model=self.sd_model, hr=True)
 
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
-- 
cgit v1.2.3


From 1c1106260300ca3956d9619875e28278b148adab Mon Sep 17 00:00:00 2001
From: papuSpartan <macabeg@icloud.com>
Date: Mon, 10 Apr 2023 03:37:15 -0500
Subject: add token merging options to infotext when necessary. Bump tomesd
 version

---
 modules/processing.py | 22 ++++++++++++++++++----
 1 file changed, 18 insertions(+), 4 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 670a7a28..95058d0b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -31,6 +31,12 @@ from einops import repeat, rearrange
 from blendmodes.blend import blendLayers, BlendType
 import tomesd
 
+# add a logger for the processing module
+logger = logging.getLogger(__name__)
+# manually set output level here since there is no option to do so yet through launch options
+# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
+
+
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
 opt_C = 4
 opt_f = 8
@@ -477,6 +483,14 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
+        "Token merging ratio": None if not (opts.token_merging or cmd_opts.token_merging) or opts.token_merging_hr_only else opts.token_merging_ratio,
+        "Token merging ratio hr": None if not (opts.token_merging or cmd_opts.token_merging) else opts.token_merging_ratio_hr,
+        "Token merging random": None if opts.token_merging_random is False else opts.token_merging_random,
+        "Token merging merge attention": None if opts.token_merging_merge_attention is True else opts.token_merging_merge_attention,
+        "Token merging merge cross attention": None if opts.token_merging_merge_cross_attention is False else opts.token_merging_merge_cross_attention,
+        "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp,
+        "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x,
+        "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y
     }
 
     generation_params.update(p.extra_generation_params)
@@ -502,16 +516,16 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 sd_vae.reload_vae_weights()
 
         if (opts.token_merging or cmd_opts.token_merging) and not opts.token_merging_hr_only:
-            print("\nApplying token merging\n")
             sd_models.apply_token_merging(sd_model=p.sd_model, hr=False)
+            logger.debug('Token merging applied')
 
         res = process_images_inner(p)
 
     finally:
         # undo model optimizations made by tomesd
         if opts.token_merging or cmd_opts.token_merging:
-            print('\nRemoving token merging model optimizations\n')
             tomesd.remove_patch(p.sd_model)
+            logger.debug('Token merging model optimizations removed')
 
         # restore opts to original state
         if p.override_settings_restore_afterwards:
@@ -954,11 +968,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             # case where user wants to use separate merge ratios
             if not opts.token_merging_hr_only:
                 # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive)
-                print('Temporarily reverting token merging optimizations in preparation for next pass')
                 tomesd.remove_patch(self.sd_model)
+                logger.debug('Temporarily removed token merging optimizations in preparation for next pass')
 
-            print("\nApplying token merging for high-res pass\n")
             sd_models.apply_token_merging(sd_model=self.sd_model, hr=True)
+            logger.debug('Applied token merging for high-res pass')
 
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
-- 
cgit v1.2.3


From e960781511eb175943be09b314ac2be46b6fc684 Mon Sep 17 00:00:00 2001
From: papuSpartan <30642826+papuSpartan@users.noreply.github.com>
Date: Wed, 3 May 2023 13:12:43 -0500
Subject: fix maximum downsampling option

---
 modules/processing.py | 1 +
 1 file changed, 1 insertion(+)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index d5d1da5a..6807a301 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -495,6 +495,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp,
         "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x,
         "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y,
+        "Token merging maximum down sampling": None if opts.token_merging_maximum_down_sampling == 1 else opts.token_merging_maximum_down_sampling,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
-- 
cgit v1.2.3


From 96d6ca4199e7c5eee8d451618de5161cea317c40 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:25:25 +0300
Subject: manual fixes for ruff

---
 modules/processing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 1a76e552..6f5233c1 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -664,7 +664,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if not shared.opts.dont_fix_second_order_samplers_schedule:
                 try:
                     step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1
-                except:
+                except Exception:
                     pass
             uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
             c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
-- 
cgit v1.2.3


From f741a98baccae100fcfb40c017b5c35c5cba1b0c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:43:42 +0300
Subject: imports cleanup for ruff

---
 modules/processing.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 6f5233c1..c3932d6b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -2,7 +2,6 @@ import json
 import math
 import os
 import sys
-import warnings
 import hashlib
 
 import torch
@@ -11,10 +10,10 @@ from PIL import Image, ImageFilter, ImageOps
 import random
 import cv2
 from skimage import exposure
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
-- 
cgit v1.2.3


From 49a55b410b66b7dd9be9335d8a2e3a71e4f8b15c Mon Sep 17 00:00:00 2001
From: Aarni Koskela <akx@iki.fi>
Date: Thu, 11 May 2023 18:28:15 +0300
Subject: Autofix Ruff W (not W605) (mostly whitespace)

---
 modules/processing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index c3932d6b..f902b9df 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -164,7 +164,7 @@ class StableDiffusionProcessing:
         self.all_subseeds = None
         self.iteration = 0
         self.is_hr_pass = False
-        
+
 
     @property
     def sd_model(self):
-- 
cgit v1.2.3


From 55e52c878ab669d5b11b001a4152ee1a3b8d4880 Mon Sep 17 00:00:00 2001
From: papuSpartan <30642826+papuSpartan@users.noreply.github.com>
Date: Sat, 13 May 2023 09:24:56 -0500
Subject: remove command line option

---
 modules/processing.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 8ba3a96b..6828e898 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -496,8 +496,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
-        "Token merging ratio": None if not (opts.token_merging or cmd_opts.token_merging) or opts.token_merging_hr_only else opts.token_merging_ratio,
-        "Token merging ratio hr": None if not (opts.token_merging or cmd_opts.token_merging) else opts.token_merging_ratio_hr,
+        "Token merging ratio": None if not opts.token_merging or opts.token_merging_hr_only else opts.token_merging_ratio,
+        "Token merging ratio hr": None if not opts.token_merging else opts.token_merging_ratio_hr,
         "Token merging random": None if opts.token_merging_random is False else opts.token_merging_random,
         "Token merging merge attention": None if opts.token_merging_merge_attention is True else opts.token_merging_merge_attention,
         "Token merging merge cross attention": None if opts.token_merging_merge_cross_attention is False else opts.token_merging_merge_cross_attention,
@@ -538,7 +538,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
-        if (opts.token_merging or cmd_opts.token_merging) and not opts.token_merging_hr_only:
+        if opts.token_merging and not opts.token_merging_hr_only:
             sd_models.apply_token_merging(sd_model=p.sd_model, hr=False)
             logger.debug('Token merging applied')
 
@@ -546,7 +546,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
     finally:
         # undo model optimizations made by tomesd
-        if opts.token_merging or cmd_opts.token_merging:
+        if opts.token_merging:
             tomesd.remove_patch(p.sd_model)
             logger.debug('Token merging model optimizations removed')
 
@@ -1004,7 +1004,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         # apply token merging optimizations from tomesd for high-res pass
         # check if hr_only so we are not redundantly patching
-        if (cmd_opts.token_merging or opts.token_merging) and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio):
+        if opts.token_merging and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio):
             # case where user wants to use separate merge ratios
             if not opts.token_merging_hr_only:
                 # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive)
-- 
cgit v1.2.3


From ac83627a31daac06f4d48b0e7db223ef807fe8e5 Mon Sep 17 00:00:00 2001
From: papuSpartan <30642826+papuSpartan@users.noreply.github.com>
Date: Sat, 13 May 2023 10:23:42 -0500
Subject: heavily simplify

---
 modules/processing.py | 35 +++++++++++++++--------------------
 1 file changed, 15 insertions(+), 20 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 6828e898..32ff61e9 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -34,7 +34,7 @@ import tomesd
 # add a logger for the processing module
 logger = logging.getLogger(__name__)
 # manually set output level here since there is no option to do so yet through launch options
-# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
+logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
 
 
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
@@ -496,15 +496,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
-        "Token merging ratio": None if not opts.token_merging or opts.token_merging_hr_only else opts.token_merging_ratio,
-        "Token merging ratio hr": None if not opts.token_merging else opts.token_merging_ratio_hr,
-        "Token merging random": None if opts.token_merging_random is False else opts.token_merging_random,
-        "Token merging merge attention": None if opts.token_merging_merge_attention is True else opts.token_merging_merge_attention,
-        "Token merging merge cross attention": None if opts.token_merging_merge_cross_attention is False else opts.token_merging_merge_cross_attention,
-        "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp,
-        "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x,
-        "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y,
-        "Token merging maximum down sampling": None if opts.token_merging_maximum_down_sampling == 1 else opts.token_merging_maximum_down_sampling,
+        "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio,
+        "Token merging ratio hr": None if not p.enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
@@ -538,15 +531,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
-        if opts.token_merging and not opts.token_merging_hr_only:
+        if opts.token_merging_ratio > 0:
             sd_models.apply_token_merging(sd_model=p.sd_model, hr=False)
-            logger.debug('Token merging applied')
+            logger.debug(f"Token merging applied to first pass. Ratio: '{opts.token_merging_ratio}'")
 
         res = process_images_inner(p)
 
     finally:
         # undo model optimizations made by tomesd
-        if opts.token_merging:
+        if opts.token_merging_ratio > 0:
             tomesd.remove_patch(p.sd_model)
             logger.debug('Token merging model optimizations removed')
 
@@ -1003,19 +996,21 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         devices.torch_gc()
 
         # apply token merging optimizations from tomesd for high-res pass
-        # check if hr_only so we are not redundantly patching
-        if opts.token_merging and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio):
-            # case where user wants to use separate merge ratios
-            if not opts.token_merging_hr_only:
-                # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive)
+        if opts.token_merging_ratio_hr > 0:
+            # in case the user has used separate merge ratios
+            if opts.token_merging_ratio > 0:
                 tomesd.remove_patch(self.sd_model)
-                logger.debug('Temporarily removed token merging optimizations in preparation for next pass')
+                logger.debug('Adjusting token merging ratio for high-res pass')
 
             sd_models.apply_token_merging(sd_model=self.sd_model, hr=True)
-            logger.debug('Applied token merging for high-res pass')
+            logger.debug(f"Applied token merging for high-res pass. Ratio: '{opts.token_merging_ratio_hr}'")
 
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
+        if opts.token_merging_ratio_hr > 0 or opts.token_merging_ratio > 0:
+            tomesd.remove_patch(self.sd_model)
+            logger.debug('Removed token merging optimizations from model')
+
         self.is_hr_pass = False
 
         return samples
-- 
cgit v1.2.3


From c2fdb44880e07f43aee2f7edc1dc36a9516501e8 Mon Sep 17 00:00:00 2001
From: papuSpartan <30642826+papuSpartan@users.noreply.github.com>
Date: Sat, 13 May 2023 11:11:02 -0500
Subject: fix for img2img

---
 modules/processing.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 32ff61e9..94fe2625 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -34,7 +34,7 @@ import tomesd
 # add a logger for the processing module
 logger = logging.getLogger(__name__)
 # manually set output level here since there is no option to do so yet through launch options
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
+# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
 
 
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
@@ -478,6 +478,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     index = position_in_batch + iteration * p.batch_size
 
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
+    enable_hr = getattr(p, 'enable_hr', False)
 
     generation_params = {
         "Steps": p.steps,
@@ -497,7 +498,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
         "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio,
-        "Token merging ratio hr": None if not p.enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
+        "Token merging ratio hr": None if not enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
-- 
cgit v1.2.3


From cdac5ace1456ba779d5a0171ff8757f31955bfee Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 16 May 2023 11:54:02 +0300
Subject: suppress ENSD infotext for samplers that don't use it

---
 modules/processing.py | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 94fe2625..15806f78 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -480,6 +480,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
     enable_hr = getattr(p, 'enable_hr', False)
 
+    uses_ensd = opts.eta_noise_seed_delta != 0
+    if uses_ensd:
+        uses_ensd = sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p)
+
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
@@ -496,17 +500,16 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
-        "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
+        "ENSD": opts.eta_noise_seed_delta if uses_ensd else None,
         "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio,
         "Token merging ratio hr": None if not enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
+        **p.extra_generation_params,
         "Version": program_version() if opts.add_version_to_infotext else None,
     }
 
-    generation_params.update(p.extra_generation_params)
-
     generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
 
     negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
-- 
cgit v1.2.3


From a61cbef02c7652f96d333b28e01f5230e225224e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 16 May 2023 12:36:15 +0300
Subject: add second_order field to sampler config

---
 modules/processing.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 15806f78..678c4468 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -681,12 +681,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     processed = Processed(p, [], p.seed, "")
                     file.write(processed.infotext(p, 0))
 
-            step_multiplier = 1
-            if not shared.opts.dont_fix_second_order_samplers_schedule:
-                try:
-                    step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1
-                except Exception:
-                    pass
+            sampler_config = sd_samplers.find_sampler_config(p.sampler_name)
+            step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
             uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
             c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
 
-- 
cgit v1.2.3


From 315f109427a5dbbf48b0da560640523800fe3c1d Mon Sep 17 00:00:00 2001
From: Aarni Koskela <akx@iki.fi>
Date: Wed, 17 May 2023 10:26:32 +0300
Subject: Copy s_min_uncond to Processed

Should fix #10416
---
 modules/processing.py | 1 +
 1 file changed, 1 insertion(+)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index 678c4468..cd63b9a6 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -316,6 +316,7 @@ class Processed:
         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.sampler_noise_scheduler_override = p.sampler_noise_scheduler_override
         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]
-- 
cgit v1.2.3


From 9fd6c1e3430f5947add23e2e94ac816c2546481c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 17 May 2023 20:22:38 +0300
Subject: move some settings to the new Optimization page add slider for token
 merging for img2img rework StableDiffusionProcessing to have the
 token_merging_ratio field fix a bug with applying png optimizations for live
 previews when they shouldn't be applied

---
 modules/processing.py | 52 +++++++++++++++++++++++++--------------------------
 1 file changed, 25 insertions(+), 27 deletions(-)

(limited to 'modules/processing.py')

diff --git a/modules/processing.py b/modules/processing.py
index cd63b9a6..2b8dd361 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -29,12 +29,6 @@ from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion
 
 from einops import repeat, rearrange
 from blendmodes.blend import blendLayers, BlendType
-import tomesd
-
-# add a logger for the processing module
-logger = logging.getLogger(__name__)
-# manually set output level here since there is no option to do so yet through launch options
-# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s')
 
 
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
@@ -156,6 +150,8 @@ class StableDiffusionProcessing:
         self.override_settings_restore_afterwards = override_settings_restore_afterwards
         self.is_using_inpainting_conditioning = False
         self.disable_extra_networks = False
+        self.token_merging_ratio = 0
+        self.token_merging_ratio_hr = 0
 
         if not seed_enable_extras:
             self.subseed = -1
@@ -171,6 +167,7 @@ class StableDiffusionProcessing:
         self.all_subseeds = None
         self.iteration = 0
         self.is_hr_pass = False
+        self.sampler = None
 
 
     @property
@@ -280,6 +277,12 @@ class StableDiffusionProcessing:
     def close(self):
         self.sampler = None
 
+    def get_token_merging_ratio(self, for_hr=False):
+        if for_hr:
+            return self.token_merging_ratio_hr or opts.token_merging_ratio_hr or self.token_merging_ratio or opts.token_merging_ratio
+
+        return self.token_merging_ratio or opts.token_merging_ratio
+
 
 class Processed:
     def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None, comments=""):
@@ -309,6 +312,8 @@ class Processed:
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
         self.clip_skip = opts.CLIP_stop_at_last_layers
+        self.token_merging_ratio = p.token_merging_ratio
+        self.token_merging_ratio_hr = p.token_merging_ratio_hr
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -367,6 +372,9 @@ class Processed:
     def infotext(self, p: StableDiffusionProcessing, index):
         return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], position_in_batch=index % self.batch_size, iteration=index // self.batch_size)
 
+    def get_token_merging_ratio(self, for_hr=False):
+        return self.token_merging_ratio_hr if for_hr else self.token_merging_ratio
+
 
 # from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3
 def slerp(val, low, high):
@@ -480,6 +488,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
 
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
     enable_hr = getattr(p, 'enable_hr', False)
+    token_merging_ratio = p.get_token_merging_ratio()
+    token_merging_ratio_hr = p.get_token_merging_ratio(for_hr=True)
 
     uses_ensd = opts.eta_noise_seed_delta != 0
     if uses_ensd:
@@ -502,8 +512,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
         "ENSD": opts.eta_noise_seed_delta if uses_ensd else None,
-        "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio,
-        "Token merging ratio hr": None if not enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
+        "Token merging ratio": None if token_merging_ratio == 0 else token_merging_ratio,
+        "Token merging ratio hr": None if not enable_hr or token_merging_ratio_hr == 0 else token_merging_ratio_hr,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
@@ -536,17 +546,12 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()
 
-        if opts.token_merging_ratio > 0:
-            sd_models.apply_token_merging(sd_model=p.sd_model, hr=False)
-            logger.debug(f"Token merging applied to first pass. Ratio: '{opts.token_merging_ratio}'")
+        sd_models.apply_token_merging(p.sd_model, p.get_token_merging_ratio())
 
         res = process_images_inner(p)
 
     finally:
-        # undo model optimizations made by tomesd
-        if opts.token_merging_ratio > 0:
-            tomesd.remove_patch(p.sd_model)
-            logger.debug('Token merging model optimizations removed')
+        sd_models.apply_token_merging(p.sd_model, 0)
 
         # restore opts to original state
         if p.override_settings_restore_afterwards:
@@ -996,21 +1001,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         x = None
         devices.torch_gc()
 
-        # apply token merging optimizations from tomesd for high-res pass
-        if opts.token_merging_ratio_hr > 0:
-            # in case the user has used separate merge ratios
-            if opts.token_merging_ratio > 0:
-                tomesd.remove_patch(self.sd_model)
-                logger.debug('Adjusting token merging ratio for high-res pass')
-
-            sd_models.apply_token_merging(sd_model=self.sd_model, hr=True)
-            logger.debug(f"Applied token merging for high-res pass. Ratio: '{opts.token_merging_ratio_hr}'")
+        sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio(for_hr=True))
 
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
-        if opts.token_merging_ratio_hr > 0 or opts.token_merging_ratio > 0:
-            tomesd.remove_patch(self.sd_model)
-            logger.debug('Removed token merging optimizations from model')
+        sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio())
 
         self.is_hr_pass = False
 
@@ -1173,3 +1168,6 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         devices.torch_gc()
 
         return samples
+
+    def get_token_merging_ratio(self, for_hr=False):
+        return self.token_merging_ratio or ("token_merging_ratio" in self.override_settings and opts.token_merging_ratio) or opts.token_merging_ratio_img2img or opts.token_merging_ratio
-- 
cgit v1.2.3