From a609bd56b4206460d1df3c3022025fc78b66718f Mon Sep 17 00:00:00 2001 From: papuSpartan 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 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 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 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 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