add token merging options to infotext when necessary. Bump tomesd

        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

    ('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')

]

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

        "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)

                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:

            # 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)

    ),

    # 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(

safetensors==0.3.0

httpcore<=0.15

fastapi==0.94.0

tomesd>=0.1.1

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tomesd>=0.1.2

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