add token merging options to infotext when necessary. Bump tomesd

version

modules/generation_parameters_copypaste.py

@@ -282,6 +282,32 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
         res["Hires resize-1"] = 0
         res["Hires resize-2"] = 0
 
+    # Infer additional override settings for token merging
+    print("inferring settings for tomesd")
+    token_merging_ratio = res.get("Token merging ratio", None)
+    token_merging_ratio_hr = res.get("Token merging ratio hr", None)
+
+    if token_merging_ratio is not None or token_merging_ratio_hr is not None:
+        res["Token merging"] = 'True'
+
+        if token_merging_ratio is None:
+            res["Token merging hr only"] = 'True'
+        else:
+            res["Token merging hr only"] = 'False'
+
+        if res.get("Token merging random", None) is None:
+            res["Token merging random"] = 'False'
+        if res.get("Token merging merge attention", None) is None:
+            res["Token merging merge attention"] = 'True'
+        if res.get("Token merging merge cross attention", None) is None:
+            res["Token merging merge cross attention"] = 'False'
+        if res.get("Token merging merge mlp", None) is None:
+            res["Token merging merge mlp"] = 'False'
+        if res.get("Token merging stride x", None) is None:
+            res["Token merging stride x"] = '2'
+        if res.get("Token merging stride y", None) is None:
+            res["Token merging stride y"] = '2'
+
     restore_old_hires_fix_params(res)
 
     return res
@@ -304,6 +330,17 @@ infotext_to_setting_name_mapping = [
     ('UniPC skip type', 'uni_pc_skip_type'),
     ('UniPC order', 'uni_pc_order'),
     ('UniPC lower order final', 'uni_pc_lower_order_final'),
+    ('Token merging', 'token_merging'),
+    ('Token merging ratio', 'token_merging_ratio'),
+    ('Token merging hr only', 'token_merging_hr_only'),
+    ('Token merging ratio hr', 'token_merging_ratio_hr'),
+    ('Token merging random', 'token_merging_random'),
+    ('Token merging merge attention', 'token_merging_merge_attention'),
+    ('Token merging merge cross attention', 'token_merging_merge_cross_attention'),
+    ('Token merging merge mlp', 'token_merging_merge_mlp'),
+    ('Token merging maximum downsampling', 'token_merging_maximum_downsampling'),
+    ('Token merging stride x', 'token_merging_stride_x'),
+    ('Token merging stride y', 'token_merging_stride_y')
 ]
 
 

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)
 

modules/shared.py

@@ -446,7 +446,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), {
     ),
     # More advanced/niche settings:
     "token_merging_random": OptionInfo(
-        True, "Use random perturbations - Disabling might help with certain samplers",
+        False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visaul artifacting.",
         gr.Checkbox
     ),
     "token_merging_merge_attention": OptionInfo(

requirements_versions.txt

@@ -28,4 +28,4 @@ torchsde==0.2.5
 safetensors==0.3.0
 httpcore<=0.15
 fastapi==0.94.0
-tomesd>=0.1.1
+tomesd>=0.1.2