diff options
| -rw-r--r-- | modules/processing.py | 29 |
1 files changed, 15 insertions, 14 deletions
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,
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