From 56680cd84ab68a283772cf697f8a72408a3f4167 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Sat, 1 Apr 2023 02:07:08 -0500 Subject: first --- modules/cmd_args.py | 4 ++++ modules/sd_models.py | 8 ++++++++ 2 files changed, 12 insertions(+) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 81c0b82a..4314f97b 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -101,3 +101,7 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers") parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False) parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False) + +# token merging / tomesd +parser.add_argument("--token-merging", action='store_true', help="Provides generation speedup by merging redundant tokens. (compatible with --xformers)", default=False) +parser.add_argument("--token-merging-ratio", type=float, help="Adjusts ratio of merged to untouched tokens. Range: (0.0-1.0], Defaults to 0.5", default=0.5) diff --git a/modules/sd_models.py b/modules/sd_models.py index 6ea874df..0b74aa0f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -9,6 +9,7 @@ from omegaconf import OmegaConf from os import mkdir from urllib import request import ldm.modules.midas as midas +import tomesd from ldm.util import instantiate_from_config @@ -430,6 +431,13 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_ try: with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd): sd_model = instantiate_from_config(sd_config.model) + + if shared.cmd_opts.token_merging: + ratio = shared.cmd_opts.token_merging_ratio + + tomesd.apply_patch(sd_model, ratio=ratio) + print(f"Model accelerated using {(ratio * 100)}% token merging via tomesd.") + timer.record("token merging") except Exception as e: pass -- cgit v1.2.3 From ef8c0440512f2fae9ceeb977b73f881c0afbb90a Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Sat, 1 Apr 2023 03:21:23 -0500 Subject: forgot to add reinstall arg back earlier since args moved out of shared --- modules/cmd_args.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 4314f97b..80df9465 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -105,3 +105,4 @@ parser.add_argument("--no-download-sd-model", action='store_true', help="don't d # token merging / tomesd parser.add_argument("--token-merging", action='store_true', help="Provides generation speedup by merging redundant tokens. (compatible with --xformers)", default=False) parser.add_argument("--token-merging-ratio", type=float, help="Adjusts ratio of merged to untouched tokens. Range: (0.0-1.0], Defaults to 0.5", default=0.5) +parser.add_argument("--reinstall-tomesd", action='store_true', help="Reinstalls tomesd", default=False) -- cgit v1.2.3 From 26ab018253cb078630fcdde47dbaee85f2466145 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Sat, 1 Apr 2023 03:31:22 -0500 Subject: delay import --- modules/sd_models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index 0b74aa0f..2c05ec17 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -9,7 +9,6 @@ from omegaconf import OmegaConf from os import mkdir from urllib import request import ldm.modules.midas as midas -import tomesd from ldm.util import instantiate_from_config @@ -433,6 +432,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_ sd_model = instantiate_from_config(sd_config.model) if shared.cmd_opts.token_merging: + import tomesd ratio = shared.cmd_opts.token_merging_ratio tomesd.apply_patch(sd_model, ratio=ratio) -- cgit v1.2.3 From 8c88bf40060c86ba508646c6d7ddc21e389be846 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Sat, 1 Apr 2023 14:12:12 -0500 Subject: use pypi package for tomesd intead of manually cloning repo --- modules/cmd_args.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 80df9465..4314f97b 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -105,4 +105,3 @@ parser.add_argument("--no-download-sd-model", action='store_true', help="don't d # token merging / tomesd parser.add_argument("--token-merging", action='store_true', help="Provides generation speedup by merging redundant tokens. (compatible with --xformers)", default=False) parser.add_argument("--token-merging-ratio", type=float, help="Adjusts ratio of merged to untouched tokens. Range: (0.0-1.0], Defaults to 0.5", default=0.5) -parser.add_argument("--reinstall-tomesd", action='store_true', help="Reinstalls tomesd", default=False) -- cgit v1.2.3 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 +++++++++++++++++++++++++++++++++++ modules/sd_models.py | 7 ------- modules/shared.py | 44 ++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 79 insertions(+), 7 deletions(-) (limited to 'modules') 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 diff --git a/modules/sd_models.py b/modules/sd_models.py index 2c05ec17..87c49b83 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -431,13 +431,6 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_ with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd): sd_model = instantiate_from_config(sd_config.model) - if shared.cmd_opts.token_merging: - import tomesd - ratio = shared.cmd_opts.token_merging_ratio - - tomesd.apply_patch(sd_model, ratio=ratio) - print(f"Model accelerated using {(ratio * 100)}% token merging via tomesd.") - timer.record("token merging") except Exception as e: pass diff --git a/modules/shared.py b/modules/shared.py index 5fd0eecb..d7379e24 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -427,6 +427,50 @@ options_templates.update(options_section((None, "Hidden options"), { "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) +options_templates.update(options_section(('token_merging', 'Token Merging'), { + "token_merging": OptionInfo( + False, "Enable redundant token merging via tomesd. (currently incompatible with controlnet extension)", + gr.Checkbox + ), + "token_merging_ratio": OptionInfo( + 0.5, "Merging Ratio", + gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} + ), + "token_merging_hr_only": OptionInfo( + True, "Apply only to high-res fix pass. Disabling can yield a ~20-35% speedup on contemporary resolutions.", + gr.Checkbox + ), + # More advanced/niche settings: + "token_merging_random": OptionInfo( + True, "Use random perturbations - Disabling might help with certain samplers", + gr.Checkbox + ), + "token_merging_merge_attention": OptionInfo( + True, "Merge attention", + gr.Checkbox + ), + "token_merging_merge_cross_attention": OptionInfo( + False, "Merge cross attention", + gr.Checkbox + ), + "token_merging_merge_mlp": OptionInfo( + False, "Merge mlp", + gr.Checkbox + ), + "token_merging_maximum_down_sampling": OptionInfo( + 1, "Maximum down sampling", + gr.Dropdown, lambda: {"choices": ["1", "2", "4", "8"]} + ), + "token_merging_stride_x": OptionInfo( + 2, "Stride - X", + gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} + ), + "token_merging_stride_y": OptionInfo( + 2, "Stride - Y", + gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} + ) +})) + options_templates.update() -- 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') 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/cmd_args.py | 3 +-- modules/processing.py | 44 +++++++++++++++----------------------------- modules/sd_models.py | 29 ++++++++++++++++++++++++++++- modules/shared.py | 6 +++++- 4 files changed, 49 insertions(+), 33 deletions(-) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 4314f97b..8e5a7fab 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -103,5 +103,4 @@ parser.add_argument("--no-hashing", action='store_true', help="disable sha256 ha parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False) # token merging / tomesd -parser.add_argument("--token-merging", action='store_true', help="Provides generation speedup by merging redundant tokens. (compatible with --xformers)", default=False) -parser.add_argument("--token-merging-ratio", type=float, help="Adjusts ratio of merged to untouched tokens. Range: (0.0-1.0], Defaults to 0.5", default=0.5) +parser.add_argument("--token-merging", action='store_true', help="Provides speed and memory improvements by merging redundant tokens. This has a more pronounced effect on higher resolutions.", default=False) 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) diff --git a/modules/sd_models.py b/modules/sd_models.py index 87c49b83..696a2333 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -16,6 +16,7 @@ from modules import paths, shared, modelloader, devices, script_callbacks, sd_va from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer +import tomesd model_dir = "Stable-diffusion" model_path = os.path.abspath(os.path.join(paths.models_path, model_dir)) @@ -545,4 +546,30 @@ def unload_model_weights(sd_model=None, info=None): print(f"Unloaded weights {timer.summary()}.") - return sd_model \ No newline at end of file + return sd_model + + +def apply_token_merging(sd_model, hr: bool): + """ + Applies speed and memory optimizations from tomesd. + + Args: + hr (bool): True if called in the context of a high-res pass + """ + + ratio = shared.opts.token_merging_ratio + if hr: + ratio = shared.opts.token_merging_ratio_hr + print("effective hr pass merge ratio is "+str(ratio)) + + tomesd.apply_patch( + sd_model, + ratio=ratio, + max_downsample=shared.opts.token_merging_maximum_down_sampling, + sx=shared.opts.token_merging_stride_x, + sy=shared.opts.token_merging_stride_y, + use_rand=shared.opts.token_merging_random, + merge_attn=shared.opts.token_merging_merge_attention, + merge_crossattn=shared.opts.token_merging_merge_cross_attention, + merge_mlp=shared.opts.token_merging_merge_mlp + ) diff --git a/modules/shared.py b/modules/shared.py index d7379e24..c7572e98 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -429,7 +429,7 @@ options_templates.update(options_section((None, "Hidden options"), { options_templates.update(options_section(('token_merging', 'Token Merging'), { "token_merging": OptionInfo( - False, "Enable redundant token merging via tomesd. (currently incompatible with controlnet extension)", + 0.5, "Enable redundant token merging via tomesd. This can provide significant speed and memory improvements.", gr.Checkbox ), "token_merging_ratio": OptionInfo( @@ -440,6 +440,10 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { True, "Apply only to high-res fix pass. Disabling can yield a ~20-35% speedup on contemporary resolutions.", gr.Checkbox ), + "token_merging_ratio_hr": OptionInfo( + 0.5, "Merging Ratio (high-res pass) - If 'Apply only to high-res' is enabled, this will always be the ratio used.", + gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} + ), # More advanced/niche settings: "token_merging_random": OptionInfo( True, "Use random perturbations - Disabling might help with certain samplers", -- cgit v1.2.3 From cf5a5773bfd1ca6a3c35232881661ec1ff4b67d7 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 4 Apr 2023 02:39:13 -0500 Subject: :p --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index c7572e98..568acdc4 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -429,7 +429,7 @@ options_templates.update(options_section((None, "Hidden options"), { options_templates.update(options_section(('token_merging', 'Token Merging'), { "token_merging": OptionInfo( - 0.5, "Enable redundant token merging via tomesd. This can provide significant speed and memory improvements.", + False, "Enable redundant token merging via tomesd. This can provide significant speed and memory improvements.", gr.Checkbox ), "token_merging_ratio": OptionInfo( -- 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/generation_parameters_copypaste.py | 37 ++++++++++++++++++++++++++++++ modules/processing.py | 22 ++++++++++++++---- modules/shared.py | 2 +- 3 files changed, 56 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6df76858..a7ede534 100644 --- a/modules/generation_parameters_copypaste.py +++ b/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') ] 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) diff --git a/modules/shared.py b/modules/shared.py index 568acdc4..d9db7317 100644 --- a/modules/shared.py +++ b/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( -- cgit v1.2.3 From c510cfd24b995f8267df3391cc961ac398922ba4 Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Mon, 10 Apr 2023 03:43:56 -0500 Subject: Update shared.py fix typo --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index d9db7317..edf11e43 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -446,7 +446,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { ), # More advanced/niche settings: "token_merging_random": OptionInfo( - False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visaul artifacting.", + False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visual artifacting.", gr.Checkbox ), "token_merging_merge_attention": OptionInfo( -- cgit v1.2.3 From a9902ca33119d6fae0a3623424bfc7ab86f2095a Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Mon, 10 Apr 2023 04:03:01 -0500 Subject: Update generation_parameters_copypaste.py --- modules/generation_parameters_copypaste.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a7ede534..ba2ca5ed 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -283,7 +283,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model 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) -- cgit v1.2.3 From dff60e2e74964a8b02b75ecd8cf8007ef67a9712 Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Mon, 10 Apr 2023 04:10:50 -0500 Subject: Update sd_models.py --- modules/sd_models.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index 696a2333..efcf730d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -560,7 +560,6 @@ def apply_token_merging(sd_model, hr: bool): ratio = shared.opts.token_merging_ratio if hr: ratio = shared.opts.token_merging_ratio_hr - print("effective hr pass merge ratio is "+str(ratio)) tomesd.apply_patch( sd_model, -- 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/generation_parameters_copypaste.py | 4 +++- modules/processing.py | 1 + modules/shared.py | 5 +---- 3 files changed, 5 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 34c1b860..83382e93 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -306,6 +306,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Token merging stride x"] = '2' if res.get("Token merging stride y", None) is None: res["Token merging stride y"] = '2' + if res.get("Token merging maximum down sampling", None) is None: + res["Token merging maximum down sampling"] = '1' restore_old_hires_fix_params(res) @@ -341,7 +343,7 @@ infotext_to_setting_name_mapping = [ ('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 maximum down sampling', 'token_merging_maximum_down_sampling'), ('Token merging stride x', 'token_merging_stride_x'), ('Token merging stride y', 'token_merging_stride_y'), ('RNG', 'randn_source'), 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, diff --git a/modules/shared.py b/modules/shared.py index 7b81ffc9..a7a72dd5 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -488,10 +488,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { False, "Merge mlp", gr.Checkbox ), - "token_merging_maximum_down_sampling": OptionInfo( - 1, "Maximum down sampling", - gr.Dropdown, lambda: {"choices": ["1", "2", "4", "8"]} - ), + "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": ['1', '2', '4', '8']}), "token_merging_stride_x": OptionInfo( 2, "Stride - X", gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} -- cgit v1.2.3 From f0efc8c211fc2d2c2f8caf6e2f92501922d18c99 Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Wed, 3 May 2023 21:10:31 -0500 Subject: not being cast properly every time, swap to ints --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index a7a72dd5..eb06909c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -488,7 +488,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { False, "Merge mlp", gr.Checkbox ), - "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": ['1', '2', '4', '8']}), + "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": [1, 2, 4, 8]}), "token_merging_stride_x": OptionInfo( 2, "Stride - X", gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} -- cgit v1.2.3 From 7fd3a4e6d7b1c70461eed0c8a7dc4f2412cdaf1c Mon Sep 17 00:00:00 2001 From: Micky Brunetti Date: Tue, 9 May 2023 15:35:57 +0200 Subject: files in vae folder with same name as a checkpoint can be found too --- modules/sd_vae.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 9b00f76e..4d2026e1 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -88,10 +88,13 @@ def refresh_vae_list(): def find_vae_near_checkpoint(checkpoint_file): - checkpoint_path = os.path.splitext(checkpoint_file)[0] - for vae_location in [checkpoint_path + ".vae.pt", checkpoint_path + ".vae.ckpt", checkpoint_path + ".vae.safetensors"]: - if os.path.isfile(vae_location): - return vae_location + checkpoint_path = os.path.basename(checkpoint_file).split('.', 1)[0] + print(f"checkpoint: {checkpoint_path}") + for vae_file in vae_dict.values(): + vae_path = os.path.basename(vae_file).split('.', 1)[0] + print(f"vae: {vae_path}") + if vae_path == checkpoint_path: + return vae_file return None -- cgit v1.2.3 From 749a93295e5259fbba2e2a849cde5a37c67aa69f Mon Sep 17 00:00:00 2001 From: Micky Brunetti Date: Tue, 9 May 2023 15:43:58 +0200 Subject: remove logs --- modules/sd_vae.py | 2 -- 1 file changed, 2 deletions(-) (limited to 'modules') diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 4d2026e1..17d1f702 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -89,10 +89,8 @@ def refresh_vae_list(): def find_vae_near_checkpoint(checkpoint_file): checkpoint_path = os.path.basename(checkpoint_file).split('.', 1)[0] - print(f"checkpoint: {checkpoint_path}") for vae_file in vae_dict.values(): vae_path = os.path.basename(vae_file).split('.', 1)[0] - print(f"vae: {vae_path}") if vae_path == checkpoint_path: return vae_file -- cgit v1.2.3 From 762265eab58cdb8f2d6398769bab43d8b8db0075 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 07:52:45 +0300 Subject: autofixes from ruff --- modules/api/api.py | 14 +++++++------- modules/extras.py | 4 ++-- modules/images.py | 4 ++-- modules/img2img.py | 2 +- modules/prompt_parser.py | 2 +- modules/realesrgan_model.py | 2 +- modules/sd_disable_initialization.py | 2 +- modules/sd_hijack.py | 4 ++-- modules/sd_hijack_ip2p.py | 2 +- modules/sd_hijack_optimizations.py | 1 - modules/sd_models.py | 6 +++--- modules/textual_inversion/textual_inversion.py | 2 +- modules/ui.py | 13 ++++++------- modules/ui_extensions.py | 2 +- modules/ui_extra_networks.py | 2 +- 15 files changed, 30 insertions(+), 32 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index 9bb95dfd..d47c39fc 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -60,7 +60,7 @@ def decode_base64_to_image(encoding): try: image = Image.open(BytesIO(base64.b64decode(encoding))) return image - except Exception as err: + except Exception: raise HTTPException(status_code=500, detail="Invalid encoded image") def encode_pil_to_base64(image): @@ -264,11 +264,11 @@ class Api: if request.alwayson_scripts and (len(request.alwayson_scripts) > 0): for alwayson_script_name in request.alwayson_scripts.keys(): alwayson_script = self.get_script(alwayson_script_name, script_runner) - if alwayson_script == None: + if alwayson_script is None: raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found") # Selectable script in always on script param check - if alwayson_script.alwayson == False: - raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params") + if alwayson_script.alwayson is False: + raise HTTPException(status_code=422, detail="Cannot have a selectable script in the always on scripts params") # always on script with no arg should always run so you don't really need to add them to the requests if "args" in request.alwayson_scripts[alwayson_script_name]: # min between arg length in scriptrunner and arg length in the request @@ -310,7 +310,7 @@ class Api: p.outpath_samples = opts.outdir_txt2img_samples shared.state.begin() - if selectable_scripts != None: + if selectable_scripts is not None: p.script_args = script_args processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here else: @@ -367,7 +367,7 @@ class Api: p.outpath_samples = opts.outdir_img2img_samples shared.state.begin() - if selectable_scripts != None: + if selectable_scripts is not None: p.script_args = script_args processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here else: @@ -642,7 +642,7 @@ class Api: sd_hijack.apply_optimizations() shared.state.end() return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") - except AssertionError as msg: + except AssertionError: shared.state.end() return TrainResponse(info=f"train embedding error: {error}") diff --git a/modules/extras.py b/modules/extras.py index ff4e9c4e..eb4f0b42 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -136,14 +136,14 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ result_is_instruct_pix2pix_model = False if theta_func2: - shared.state.textinfo = f"Loading B" + shared.state.textinfo = "Loading B" print(f"Loading {secondary_model_info.filename}...") theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu') else: theta_1 = None if theta_func1: - shared.state.textinfo = f"Loading C" + shared.state.textinfo = "Loading C" print(f"Loading {tertiary_model_info.filename}...") theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu') diff --git a/modules/images.py b/modules/images.py index a41965ab..3d5d76cc 100644 --- a/modules/images.py +++ b/modules/images.py @@ -409,13 +409,13 @@ class FilenameGenerator: time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format try: time_zone = pytz.timezone(args[1]) if len(args) > 1 else None - except pytz.exceptions.UnknownTimeZoneError as _: + except pytz.exceptions.UnknownTimeZoneError: time_zone = None time_zone_time = time_datetime.astimezone(time_zone) try: formatted_time = time_zone_time.strftime(time_format) - except (ValueError, TypeError) as _: + except (ValueError, TypeError): formatted_time = time_zone_time.strftime(self.default_time_format) return sanitize_filename_part(formatted_time, replace_spaces=False) diff --git a/modules/img2img.py b/modules/img2img.py index 9fc3a698..cdae301a 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): # try to find corresponding mask for an image using simple filename matching mask_image_path = os.path.join(inpaint_mask_dir, os.path.basename(image)) # if not found use first one ("same mask for all images" use-case) - if not mask_image_path in inpaint_masks: + if mask_image_path not in inpaint_masks: mask_image_path = inpaint_masks[0] mask_image = Image.open(mask_image_path) p.image_mask = mask_image diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index 69665372..e084e948 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -92,7 +92,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): def get_schedule(prompt): try: tree = schedule_parser.parse(prompt) - except lark.exceptions.LarkError as e: + except lark.exceptions.LarkError: if 0: import traceback traceback.print_exc() diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index efd7fca5..9ec1adf2 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -134,6 +134,6 @@ def get_realesrgan_models(scaler): ), ] return models - except Exception as e: + except Exception: print("Error making Real-ESRGAN models list:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index c4a09d15..9fc89dc6 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -61,7 +61,7 @@ class DisableInitialization: if res is None: res = original(url, *args, local_files_only=False, **kwargs) return res - except Exception as e: + except Exception: return original(url, *args, local_files_only=False, **kwargs) def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs): diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index f4bb0266..d8135211 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -118,7 +118,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): try: #Delete temporary weights if appended del sd_model._custom_loss_weight - except AttributeError as e: + except AttributeError: pass #If we have an old loss function, reset the loss function to the original one @@ -133,7 +133,7 @@ def apply_weighted_forward(sd_model): def undo_weighted_forward(sd_model): try: del sd_model.weighted_forward - except AttributeError as e: + except AttributeError: pass diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py index 3c727d3b..41ed54a2 100644 --- a/modules/sd_hijack_ip2p.py +++ b/modules/sd_hijack_ip2p.py @@ -10,4 +10,4 @@ def should_hijack_ip2p(checkpoint_info): ckpt_basename = os.path.basename(checkpoint_info.filename).lower() cfg_basename = os.path.basename(sd_models_config.find_checkpoint_config_near_filename(checkpoint_info)).lower() - return "pix2pix" in ckpt_basename and not "pix2pix" in cfg_basename + return "pix2pix" in ckpt_basename and "pix2pix" not in cfg_basename diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index f10865cd..b623d53d 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -296,7 +296,6 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_ if chunk_threshold_bytes is not None and qk_matmul_size_bytes <= chunk_threshold_bytes: # the big matmul fits into our memory limit; do everything in 1 chunk, # i.e. send it down the unchunked fast-path - query_chunk_size = q_tokens kv_chunk_size = k_tokens with devices.without_autocast(disable=q.dtype == v.dtype): diff --git a/modules/sd_models.py b/modules/sd_models.py index 36f643e1..11c1a344 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -239,7 +239,7 @@ def read_metadata_from_safetensors(filename): if isinstance(v, str) and v[0:1] == '{': try: res[k] = json.loads(v) - except Exception as e: + except Exception: pass return res @@ -467,7 +467,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): try: with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd): sd_model = instantiate_from_config(sd_config.model) - except Exception as e: + except Exception: pass if sd_model is None: @@ -544,7 +544,7 @@ def reload_model_weights(sd_model=None, info=None): try: load_model_weights(sd_model, checkpoint_info, state_dict, timer) - except Exception as e: + except Exception: print("Failed to load checkpoint, restoring previous") load_model_weights(sd_model, current_checkpoint_info, None, timer) raise diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 4368eb63..f753b75f 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -603,7 +603,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st try: vectorSize = list(data['string_to_param'].values())[0].shape[0] - except Exception as e: + except Exception: vectorSize = '?' checkpoint = sd_models.select_checkpoint() diff --git a/modules/ui.py b/modules/ui.py index d02f6e82..2171f3aa 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -246,7 +246,7 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: all_seeds = gen_info.get('all_seeds', [-1]) res = all_seeds[index if 0 <= index < len(all_seeds) else 0] - except json.decoder.JSONDecodeError as e: + except json.decoder.JSONDecodeError: if gen_info_string != '': print("Error parsing JSON generation info:", file=sys.stderr) print(gen_info_string, file=sys.stderr) @@ -736,8 +736,8 @@ def create_ui(): with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch: hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' gr.HTML( - f"

Process images in a directory on the same machine where the server is running." + - f"
Use an empty output directory to save pictures normally instead of writing to the output directory." + + "

Process images in a directory on the same machine where the server is running." + + "
Use an empty output directory to save pictures normally instead of writing to the output directory." + f"
Add inpaint batch mask directory to enable inpaint batch processing." f"{hidden}

" ) @@ -746,7 +746,6 @@ def create_ui(): img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir") img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch] - img2img_image_inputs = [init_img, sketch, init_img_with_mask, inpaint_color_sketch] for i, tab in enumerate(img2img_tabs): tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab]) @@ -1290,8 +1289,8 @@ def create_ui(): with gr.Column(elem_id='ti_gallery_container'): ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) - ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) - ti_progress = gr.HTML(elem_id="ti_progress", value="") + gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) + gr.HTML(elem_id="ti_progress", value="") ti_outcome = gr.HTML(elem_id="ti_error", value="") create_embedding.click( @@ -1668,7 +1667,7 @@ def create_ui(): interface.render() if os.path.exists(os.path.join(script_path, "notification.mp3")): - audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) + gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) footer = shared.html("footer.html") footer = footer.format(versions=versions_html()) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index d9faf85a..ed70abe5 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -490,7 +490,7 @@ def create_ui(): config_states.list_config_states() with gr.Blocks(analytics_enabled=False) as ui: - with gr.Tabs(elem_id="tabs_extensions") as tabs: + with gr.Tabs(elem_id="tabs_extensions"): with gr.TabItem("Installed", id="installed"): with gr.Row(elem_id="extensions_installed_top"): diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 8c3dea56..49e06289 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -263,7 +263,7 @@ def create_ui(container, button, tabname): ui.stored_extra_pages = pages_in_preferred_order(extra_pages.copy()) ui.tabname = tabname - with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs: + with gr.Tabs(elem_id=tabname+"_extra_tabs"): for page in ui.stored_extra_pages: page_id = page.title.lower().replace(" ", "_") -- 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/api/api.py | 129 +++++++++++++++-------------- modules/api/models.py | 5 +- modules/codeformer/codeformer_arch.py | 2 +- modules/esrgan_model_arch.py | 2 + modules/extra_networks_hypernet.py | 2 +- modules/images.py | 4 +- modules/img2img.py | 1 - modules/interrogate.py | 1 - modules/modelloader.py | 6 +- modules/models/diffusion/ddpm_edit.py | 26 +++--- modules/models/diffusion/uni_pc/sampler.py | 3 +- modules/processing.py | 2 +- modules/prompt_parser.py | 11 ++- modules/textual_inversion/autocrop.py | 2 +- modules/ui.py | 8 +- modules/upscaler.py | 2 +- 16 files changed, 101 insertions(+), 105 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index d47c39fc..f52d371b 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -15,7 +15,8 @@ from secrets import compare_digest import modules.shared as shared from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing -from modules.api.models import * +from modules.api import models +from modules.shared import opts from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images from modules.textual_inversion.textual_inversion import create_embedding, train_embedding from modules.textual_inversion.preprocess import preprocess @@ -25,20 +26,21 @@ from modules.sd_models import checkpoints_list, unload_model_weights, reload_mod from modules.sd_models_config import find_checkpoint_config_near_filename from modules.realesrgan_model import get_realesrgan_models from modules import devices -from typing import List +from typing import Dict, List, Any import piexif import piexif.helper + def upscaler_to_index(name: str): try: return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in sd_upscalers])}") + except Exception: + raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) - except: + except Exception: raise HTTPException(status_code=422, detail=f"Script '{name}' not found") def validate_sampler_name(name): @@ -99,7 +101,7 @@ def api_middleware(app: FastAPI): import starlette # importing just so it can be placed on silent list from rich.console import Console console = Console() - except: + except Exception: import traceback rich_available = False @@ -166,36 +168,36 @@ class Api: self.app = app self.queue_lock = queue_lock api_middleware(self.app) - self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse) - self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse) - self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse) - self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse) - self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse) - self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse) + self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse) + self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse) + self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse) + self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse) + self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse) + self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse) self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"]) self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"]) self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"]) - self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel) + self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel) self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"]) - self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel) - self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) - self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) - self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) - self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem]) - self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem]) - self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem]) - self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem]) - self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse) + self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel) + self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem]) + self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem]) + self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem]) + self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem]) + self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem]) + self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem]) + self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem]) + self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse) self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"]) - self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse) - self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse) - self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=PreprocessResponse) - self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse) - self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse) - self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse) + self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse) + self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse) + self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse) + self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse) + self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse) + self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse) self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"]) self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"]) - self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList) + self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList) self.default_script_arg_txt2img = [] self.default_script_arg_img2img = [] @@ -224,7 +226,7 @@ class Api: t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] - return ScriptsList(txt2img = t2ilist, img2img = i2ilist) + return models.ScriptsList(txt2img=t2ilist, img2img=i2ilist) def get_script(self, script_name, script_runner): if script_name is None or script_name == "": @@ -276,7 +278,7 @@ class Api: script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx] return script_args - def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): + def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI): script_runner = scripts.scripts_txt2img if not script_runner.scripts: script_runner.initialize_scripts(False) @@ -320,9 +322,9 @@ class Api: b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] - return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) + return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) - def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI): + def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI): init_images = img2imgreq.init_images if init_images is None: raise HTTPException(status_code=404, detail="Init image not found") @@ -381,9 +383,9 @@ class Api: img2imgreq.init_images = None img2imgreq.mask = None - return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) + return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) - def extras_single_image_api(self, req: ExtrasSingleImageRequest): + def extras_single_image_api(self, req: models.ExtrasSingleImageRequest): reqDict = setUpscalers(req) reqDict['image'] = decode_base64_to_image(reqDict['image']) @@ -391,9 +393,9 @@ class Api: with self.queue_lock: result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict) - return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) + return models.ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) - def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): + def extras_batch_images_api(self, req: models.ExtrasBatchImagesRequest): reqDict = setUpscalers(req) image_list = reqDict.pop('imageList', []) @@ -402,15 +404,15 @@ class Api: with self.queue_lock: result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict) - return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) + return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) - def pnginfoapi(self, req: PNGInfoRequest): + def pnginfoapi(self, req: models.PNGInfoRequest): if(not req.image.strip()): - return PNGInfoResponse(info="") + return models.PNGInfoResponse(info="") image = decode_base64_to_image(req.image.strip()) if image is None: - return PNGInfoResponse(info="") + return models.PNGInfoResponse(info="") geninfo, items = images.read_info_from_image(image) if geninfo is None: @@ -418,13 +420,13 @@ class Api: items = {**{'parameters': geninfo}, **items} - return PNGInfoResponse(info=geninfo, items=items) + return models.PNGInfoResponse(info=geninfo, items=items) - def progressapi(self, req: ProgressRequest = Depends()): + def progressapi(self, req: models.ProgressRequest = Depends()): # copy from check_progress_call of ui.py if shared.state.job_count == 0: - return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo) + return models.ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo) # avoid dividing zero progress = 0.01 @@ -446,9 +448,9 @@ class Api: if shared.state.current_image and not req.skip_current_image: current_image = encode_pil_to_base64(shared.state.current_image) - return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo) + return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo) - def interrogateapi(self, interrogatereq: InterrogateRequest): + def interrogateapi(self, interrogatereq: models.InterrogateRequest): image_b64 = interrogatereq.image if image_b64 is None: raise HTTPException(status_code=404, detail="Image not found") @@ -465,7 +467,7 @@ class Api: else: raise HTTPException(status_code=404, detail="Model not found") - return InterrogateResponse(caption=processed) + return models.InterrogateResponse(caption=processed) def interruptapi(self): shared.state.interrupt() @@ -570,36 +572,36 @@ class Api: filename = create_embedding(**args) # create empty embedding sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used shared.state.end() - return CreateResponse(info=f"create embedding filename: {filename}") + return models.CreateResponse(info=f"create embedding filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info=f"create embedding error: {e}") + return models.TrainResponse(info=f"create embedding error: {e}") def create_hypernetwork(self, args: dict): try: shared.state.begin() filename = create_hypernetwork(**args) # create empty embedding shared.state.end() - return CreateResponse(info=f"create hypernetwork filename: {filename}") + return models.CreateResponse(info=f"create hypernetwork filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info=f"create hypernetwork error: {e}") + return models.TrainResponse(info=f"create hypernetwork error: {e}") def preprocess(self, args: dict): try: shared.state.begin() preprocess(**args) # quick operation unless blip/booru interrogation is enabled shared.state.end() - return PreprocessResponse(info = 'preprocess complete') + return models.PreprocessResponse(info = 'preprocess complete') except KeyError as e: shared.state.end() - return PreprocessResponse(info=f"preprocess error: invalid token: {e}") + return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}") except AssertionError as e: shared.state.end() - return PreprocessResponse(info=f"preprocess error: {e}") + return models.PreprocessResponse(info=f"preprocess error: {e}") except FileNotFoundError as e: shared.state.end() - return PreprocessResponse(info=f'preprocess error: {e}') + return models.PreprocessResponse(info=f'preprocess error: {e}') def train_embedding(self, args: dict): try: @@ -617,10 +619,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") + return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info=f"train embedding error: {msg}") + return models.TrainResponse(info=f"train embedding error: {msg}") def train_hypernetwork(self, args: dict): try: @@ -641,14 +643,15 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") + return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError: shared.state.end() - return TrainResponse(info=f"train embedding error: {error}") + return models.TrainResponse(info=f"train embedding error: {error}") def get_memory(self): try: - import os, psutil + import os + import psutil process = psutil.Process(os.getpid()) res = process.memory_info() # only rss is cross-platform guaranteed so we dont rely on other values ram_total = 100 * res.rss / process.memory_percent() # and total memory is calculated as actual value is not cross-platform safe @@ -675,10 +678,10 @@ class Api: 'events': warnings, } else: - cuda = { 'error': 'unavailable' } + cuda = {'error': 'unavailable'} except Exception as err: - cuda = { 'error': f'{err}' } - return MemoryResponse(ram = ram, cuda = cuda) + cuda = {'error': f'{err}'} + return models.MemoryResponse(ram=ram, cuda=cuda) def launch(self, server_name, port): self.app.include_router(self.router) diff --git a/modules/api/models.py b/modules/api/models.py index 4a70f440..4d291076 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -223,8 +223,9 @@ for key in _options: if(_options[key].dest != 'help'): flag = _options[key] _type = str - if _options[key].default is not None: _type = type(_options[key].default) - flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))}) + if _options[key].default is not None: + _type = type(_options[key].default) + flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))}) FlagsModel = create_model("Flags", **flags) diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 11dcc3ee..f1a7cf09 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -7,7 +7,7 @@ from torch import nn, Tensor import torch.nn.functional as F from typing import Optional, List -from modules.codeformer.vqgan_arch import * +from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 6071fea7..7f8bc7c0 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -438,9 +438,11 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias= padding = padding if pad_type == 'zero' else 0 if convtype=='PartialConv2D': + from torchvision.ops import PartialConv2d # this is definitely not going to work, but PartialConv2d doesn't work anyway and this shuts up static analyzer c = PartialConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation, bias=bias, groups=groups) elif convtype=='DeformConv2D': + from torchvision.ops import DeformConv2d # not tested c = DeformConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation, bias=bias, groups=groups) elif convtype=='Conv3D': diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index 04f27c9f..aa2a14ef 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -1,4 +1,4 @@ -from modules import extra_networks, shared, extra_networks +from modules import extra_networks, shared from modules.hypernetworks import hypernetwork diff --git a/modules/images.py b/modules/images.py index 3d5d76cc..5eb6d855 100644 --- a/modules/images.py +++ b/modules/images.py @@ -472,9 +472,9 @@ def get_next_sequence_number(path, basename): prefix_length = len(basename) for p in os.listdir(path): if p.startswith(basename): - l = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element) + parts = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element) try: - result = max(int(l[0]), result) + result = max(int(parts[0]), result) except ValueError: pass diff --git a/modules/img2img.py b/modules/img2img.py index cdae301a..32b1ecd6 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -13,7 +13,6 @@ from modules.shared import opts, state import modules.shared as shared import modules.processing as processing from modules.ui import plaintext_to_html -import modules.images as images import modules.scripts diff --git a/modules/interrogate.py b/modules/interrogate.py index 9f7d657f..22df9216 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -11,7 +11,6 @@ import torch.hub from torchvision import transforms from torchvision.transforms.functional import InterpolationMode -import modules.shared as shared from modules import devices, paths, shared, lowvram, modelloader, errors blip_image_eval_size = 384 diff --git a/modules/modelloader.py b/modules/modelloader.py index cb85ac4f..cf685000 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -108,12 +108,12 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None): print(f"Moving {file} from {src_path} to {dest_path}.") try: shutil.move(fullpath, dest_path) - except: + except Exception: pass if len(os.listdir(src_path)) == 0: print(f"Removing empty folder: {src_path}") shutil.rmtree(src_path, True) - except: + except Exception: pass @@ -141,7 +141,7 @@ def load_upscalers(): full_model = f"modules.{model_name}_model" try: importlib.import_module(full_model) - except: + except Exception: pass datas = [] diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index f880bc3c..611c2b69 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -479,7 +479,7 @@ class LatentDiffusion(DDPM): self.cond_stage_key = cond_stage_key try: self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1 - except: + except Exception: self.num_downs = 0 if not scale_by_std: self.scale_factor = scale_factor @@ -891,16 +891,6 @@ class LatentDiffusion(DDPM): c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float())) return self.p_losses(x, c, t, *args, **kwargs) - def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset - def rescale_bbox(bbox): - x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2]) - y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3]) - w = min(bbox[2] / crop_coordinates[2], 1 - x0) - h = min(bbox[3] / crop_coordinates[3], 1 - y0) - return x0, y0, w, h - - return [rescale_bbox(b) for b in bboxes] - def apply_model(self, x_noisy, t, cond, return_ids=False): if isinstance(cond, dict): @@ -1171,8 +1161,10 @@ class LatentDiffusion(DDPM): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(x0_partial) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) return img, intermediates @torch.no_grad() @@ -1219,8 +1211,10 @@ class LatentDiffusion(DDPM): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(img) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) if return_intermediates: return img, intermediates @@ -1337,7 +1331,7 @@ class LatentDiffusion(DDPM): if inpaint: # make a simple center square - b, h, w = z.shape[0], z.shape[2], z.shape[3] + h, w = z.shape[2], z.shape[3] mask = torch.ones(N, h, w).to(self.device) # zeros will be filled in mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0. diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py index a241c8a7..0a9defa1 100644 --- a/modules/models/diffusion/uni_pc/sampler.py +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -54,7 +54,8 @@ class UniPCSampler(object): if conditioning is not None: if isinstance(conditioning, dict): ctmp = conditioning[list(conditioning.keys())[0]] - while isinstance(ctmp, list): ctmp = ctmp[0] + while isinstance(ctmp, list): + ctmp = ctmp[0] cbs = ctmp.shape[0] if cbs != batch_size: print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") 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) diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index e084e948..3a720721 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -54,18 +54,21 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): """ def collect_steps(steps, tree): - l = [steps] + res = [steps] + class CollectSteps(lark.Visitor): def scheduled(self, tree): tree.children[-1] = float(tree.children[-1]) if tree.children[-1] < 1: tree.children[-1] *= steps tree.children[-1] = min(steps, int(tree.children[-1])) - l.append(tree.children[-1]) + res.append(tree.children[-1]) + def alternate(self, tree): - l.extend(range(1, steps+1)) + res.extend(range(1, steps+1)) + CollectSteps().visit(tree) - return sorted(set(l)) + return sorted(set(res)) def at_step(step, tree): class AtStep(lark.Transformer): diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index ba1bdcd4..d7d8d2e3 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -185,7 +185,7 @@ def image_face_points(im, settings): try: faces = classifier.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE) - except: + except Exception: continue if len(faces) > 0: diff --git a/modules/ui.py b/modules/ui.py index 2171f3aa..6beda76f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1,15 +1,9 @@ -import html import json -import math import mimetypes import os -import platform -import random import sys -import tempfile -import time import traceback -from functools import partial, reduce +from functools import reduce import warnings import gradio as gr diff --git a/modules/upscaler.py b/modules/upscaler.py index e2eaa730..0ad4fe99 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -45,7 +45,7 @@ class Upscaler: try: import cv2 self.can_tile = True - except: + except Exception: pass @abstractmethod -- 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/codeformer/codeformer_arch.py | 4 +--- modules/codeformer/vqgan_arch.py | 2 -- modules/codeformer_model.py | 4 +--- modules/config_states.py | 2 +- modules/esrgan_model.py | 2 +- modules/esrgan_model_arch.py | 1 - modules/extensions.py | 1 - modules/generation_parameters_copypaste.py | 4 ---- modules/hypernetworks/hypernetwork.py | 3 +-- modules/hypernetworks/ui.py | 2 -- modules/images.py | 2 +- modules/img2img.py | 5 +---- modules/mac_specific.py | 1 - modules/modelloader.py | 1 - modules/models/diffusion/uni_pc/uni_pc.py | 1 - modules/processing.py | 5 ++--- modules/sd_hijack.py | 2 +- modules/sd_hijack_inpainting.py | 6 ------ modules/sd_hijack_ip2p.py | 5 +---- modules/sd_hijack_xlmr.py | 2 -- modules/sd_models.py | 2 +- modules/sd_models_config.py | 1 - modules/sd_samplers_kdiffusion.py | 1 - modules/sd_vae.py | 3 --- modules/shared.py | 3 --- modules/styles.py | 9 --------- modules/textual_inversion/autocrop.py | 4 +--- modules/textual_inversion/image_embedding.py | 2 +- modules/textual_inversion/preprocess.py | 4 ---- modules/textual_inversion/textual_inversion.py | 1 - modules/txt2img.py | 9 +++------ modules/ui.py | 5 ++--- modules/ui_extra_networks.py | 1 - modules/ui_postprocessing.py | 2 +- modules/upscaler.py | 2 -- modules/xlmr.py | 2 +- 36 files changed, 21 insertions(+), 85 deletions(-) (limited to 'modules') diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index f1a7cf09..00c407de 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -1,14 +1,12 @@ # this file is copied from CodeFormer repository. Please see comment in modules/codeformer_model.py import math -import numpy as np import torch from torch import nn, Tensor import torch.nn.functional as F -from typing import Optional, List +from typing import Optional from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock -from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY def calc_mean_std(feat, eps=1e-5): diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index e7293683..820e6b12 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -5,11 +5,9 @@ VQGAN code, adapted from the original created by the Unleashing Transformers aut https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py ''' -import numpy as np import torch import torch.nn as nn import torch.nn.functional as F -import copy from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 8d84bbc9..8e56cb89 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -33,11 +33,9 @@ def setup_model(dirname): try: from torchvision.transforms.functional import normalize from modules.codeformer.codeformer_arch import CodeFormer - from basicsr.utils.download_util import load_file_from_url - from basicsr.utils import imwrite, img2tensor, tensor2img + from basicsr.utils import img2tensor, tensor2img from facelib.utils.face_restoration_helper import FaceRestoreHelper from facelib.detection.retinaface import retinaface - from modules.shared import cmd_opts net_class = CodeFormer diff --git a/modules/config_states.py b/modules/config_states.py index 2ea00929..8f1ff428 100644 --- a/modules/config_states.py +++ b/modules/config_states.py @@ -14,7 +14,7 @@ from collections import OrderedDict import git from modules import shared, extensions -from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path, config_states_dir +from modules.paths_internal import script_path, config_states_dir all_config_states = OrderedDict() diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index f4369257..85aa6934 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -6,7 +6,7 @@ from PIL import Image from basicsr.utils.download_util import load_file_from_url import modules.esrgan_model_arch as arch -from modules import shared, modelloader, images, devices +from modules import modelloader, images, devices from modules.upscaler import Upscaler, UpscalerData from modules.shared import opts diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 7f8bc7c0..4de9dd8d 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -2,7 +2,6 @@ from collections import OrderedDict import math -import functools import torch import torch.nn as nn import torch.nn.functional as F diff --git a/modules/extensions.py b/modules/extensions.py index 34d9d654..829f8cd9 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -3,7 +3,6 @@ import sys import traceback import time -from datetime import datetime import git from modules import shared diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index fe8b18b2..f1c59c46 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -1,15 +1,11 @@ import base64 -import html import io -import math import os import re -from pathlib import Path import gradio as gr from modules.paths import data_path from modules import shared, ui_tempdir, script_callbacks -import tempfile from PIL import Image re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)' diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 1fc49537..9fe749b7 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -1,4 +1,3 @@ -import csv import datetime import glob import html @@ -18,7 +17,7 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler from torch import einsum from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_ -from collections import defaultdict, deque +from collections import deque from statistics import stdev, mean diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 76599f5a..be168736 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -1,6 +1,4 @@ import html -import os -import re import gradio as gr import modules.hypernetworks.hypernetwork diff --git a/modules/images.py b/modules/images.py index 5eb6d855..7392cb8b 100644 --- a/modules/images.py +++ b/modules/images.py @@ -19,7 +19,7 @@ import json import hashlib from modules import sd_samplers, shared, script_callbacks, errors -from modules.shared import opts, cmd_opts +from modules.shared import opts LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) diff --git a/modules/img2img.py b/modules/img2img.py index 32b1ecd6..d704bf90 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -1,12 +1,9 @@ -import math import os -import sys -import traceback import numpy as np from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError -from modules import devices, sd_samplers +from modules import sd_samplers from modules.generation_parameters_copypaste import create_override_settings_dict from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images from modules.shared import opts, state diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 40ce2101..5c2f92a1 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -1,6 +1,5 @@ import torch import platform -from modules import paths from modules.sd_hijack_utils import CondFunc from packaging import version diff --git a/modules/modelloader.py b/modules/modelloader.py index cf685000..92ada694 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -1,4 +1,3 @@ -import glob import os import shutil import importlib diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index 11b330bc..a4c4ef4e 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -1,5 +1,4 @@ import torch -import torch.nn.functional as F import math from tqdm.auto import trange 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 diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index d8135211..81573b78 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -3,7 +3,7 @@ from torch.nn.functional import silu from types import MethodType import modules.textual_inversion.textual_inversion -from modules import devices, sd_hijack_optimizations, shared, sd_hijack_checkpoint +from modules import devices, sd_hijack_optimizations, shared from modules.hypernetworks import hypernetwork from modules.shared import cmd_opts from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 55a2ce4d..344d75c8 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -1,15 +1,9 @@ -import os import torch -from einops import repeat -from omegaconf import ListConfig - import ldm.models.diffusion.ddpm import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from ldm.models.diffusion.ddpm import LatentDiffusion -from ldm.models.diffusion.plms import PLMSSampler from ldm.models.diffusion.ddim import DDIMSampler, noise_like from ldm.models.diffusion.sampling_util import norm_thresholding diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py index 41ed54a2..6fe6b6ff 100644 --- a/modules/sd_hijack_ip2p.py +++ b/modules/sd_hijack_ip2p.py @@ -1,8 +1,5 @@ -import collections import os.path -import sys -import gc -import time + def should_hijack_ip2p(checkpoint_info): from modules import sd_models_config diff --git a/modules/sd_hijack_xlmr.py b/modules/sd_hijack_xlmr.py index 4ac51c38..28528329 100644 --- a/modules/sd_hijack_xlmr.py +++ b/modules/sd_hijack_xlmr.py @@ -1,8 +1,6 @@ -import open_clip.tokenizer import torch from modules import sd_hijack_clip, devices -from modules.shared import opts class FrozenXLMREmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords): diff --git a/modules/sd_models.py b/modules/sd_models.py index 11c1a344..1c09c709 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -565,7 +565,7 @@ def reload_model_weights(sd_model=None, info=None): def unload_model_weights(sd_model=None, info=None): - from modules import lowvram, devices, sd_hijack + from modules import devices, sd_hijack timer = Timer() if model_data.sd_model: diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 7a79925a..9bfe1237 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -1,4 +1,3 @@ -import re import os import torch diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 0fc9f456..3b8e9622 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -1,7 +1,6 @@ from collections import deque import torch import inspect -import einops import k_diffusion.sampling from modules import prompt_parser, devices, sd_samplers_common diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 521e485a..b7176125 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -1,8 +1,5 @@ -import torch -import safetensors.torch import os import collections -from collections import namedtuple from modules import paths, shared, devices, script_callbacks, sd_models import glob from copy import deepcopy diff --git a/modules/shared.py b/modules/shared.py index 4631965b..44cd2c0c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -1,12 +1,9 @@ -import argparse import datetime import json import os import sys import time -import requests -from PIL import Image import gradio as gr import tqdm diff --git a/modules/styles.py b/modules/styles.py index 11642075..c22769cf 100644 --- a/modules/styles.py +++ b/modules/styles.py @@ -1,18 +1,9 @@ -# We need this so Python doesn't complain about the unknown StableDiffusionProcessing-typehint at runtime -from __future__ import annotations - import csv import os import os.path import typing -import collections.abc as abc -import tempfile import shutil -if typing.TYPE_CHECKING: - # Only import this when code is being type-checked, it doesn't have any effect at runtime - from .processing import StableDiffusionProcessing - class PromptStyle(typing.NamedTuple): name: str diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index d7d8d2e3..7770d22f 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -1,10 +1,8 @@ import cv2 import requests import os -from collections import defaultdict -from math import log, sqrt import numpy as np -from PIL import Image, ImageDraw +from PIL import ImageDraw GREEN = "#0F0" BLUE = "#00F" diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py index 5593f88c..ee0e850a 100644 --- a/modules/textual_inversion/image_embedding.py +++ b/modules/textual_inversion/image_embedding.py @@ -2,7 +2,7 @@ import base64 import json import numpy as np import zlib -from PIL import Image, PngImagePlugin, ImageDraw, ImageFont +from PIL import Image, ImageDraw, ImageFont from fonts.ttf import Roboto import torch from modules.shared import opts diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index da0bcb26..d0cad09e 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -1,13 +1,9 @@ import os from PIL import Image, ImageOps import math -import platform -import sys import tqdm -import time from modules import paths, shared, images, deepbooru -from modules.shared import opts, cmd_opts from modules.textual_inversion import autocrop diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index f753b75f..9ed9ba45 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -1,7 +1,6 @@ import os import sys import traceback -import inspect from collections import namedtuple import torch diff --git a/modules/txt2img.py b/modules/txt2img.py index 16841d0f..f022381c 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -1,18 +1,15 @@ import modules.scripts -from modules import sd_samplers +from modules import sd_samplers, processing from modules.generation_parameters_copypaste import create_override_settings_dict -from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \ - StableDiffusionProcessingImg2Img, process_images from modules.shared import opts, cmd_opts import modules.shared as shared -import modules.processing as processing from modules.ui import plaintext_to_html def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args): override_settings = create_override_settings_dict(override_settings_texts) - p = StableDiffusionProcessingTxt2Img( + p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids, @@ -53,7 +50,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p) + processed = processing.process_images(p) p.close() diff --git a/modules/ui.py b/modules/ui.py index 6beda76f..f7e57593 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -14,10 +14,10 @@ from PIL import Image, PngImagePlugin from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress -from modules.ui_components import FormRow, FormColumn, FormGroup, ToolButton, FormHTML +from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path -from modules.shared import opts, cmd_opts, restricted_opts +from modules.shared import opts, cmd_opts import modules.codeformer_model import modules.generation_parameters_copypaste as parameters_copypaste @@ -28,7 +28,6 @@ import modules.shared as shared import modules.styles import modules.textual_inversion.ui from modules import prompt_parser -from modules.images import save_image from modules.sd_hijack import model_hijack from modules.sd_samplers import samplers, samplers_for_img2img from modules.textual_inversion import textual_inversion diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 49e06289..800e467a 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -1,4 +1,3 @@ -import glob import os.path import urllib.parse from pathlib import Path diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py index f25639e5..c7dc1154 100644 --- a/modules/ui_postprocessing.py +++ b/modules/ui_postprocessing.py @@ -1,5 +1,5 @@ import gradio as gr -from modules import scripts_postprocessing, scripts, shared, gfpgan_model, codeformer_model, ui_common, postprocessing, call_queue +from modules import scripts, shared, ui_common, postprocessing, call_queue import modules.generation_parameters_copypaste as parameters_copypaste diff --git a/modules/upscaler.py b/modules/upscaler.py index 0ad4fe99..777593b0 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -2,8 +2,6 @@ import os from abc import abstractmethod import PIL -import numpy as np -import torch from PIL import Image import modules.shared diff --git a/modules/xlmr.py b/modules/xlmr.py index beab3fdf..e056c3f6 100644 --- a/modules/xlmr.py +++ b/modules/xlmr.py @@ -1,4 +1,4 @@ -from transformers import BertPreTrainedModel,BertModel,BertConfig +from transformers import BertPreTrainedModel, BertConfig import torch.nn as nn import torch from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig -- cgit v1.2.3 From 4b854806d98cf5ccd48e5cd99c172613da7937f0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 09:02:23 +0300 Subject: F401 fixes for ruff --- modules/cmd_args.py | 2 +- modules/deepbooru.py | 1 - modules/extensions.py | 2 +- modules/gfpgan_model.py | 2 +- modules/models/diffusion/uni_pc/__init__.py | 2 +- modules/paths.py | 4 ++-- modules/realesrgan_model.py | 6 +++--- modules/script_loading.py | 1 - modules/sd_hijack_inpainting.py | 2 +- modules/sd_models.py | 4 +--- modules/sd_samplers.py | 2 +- modules/shared.py | 2 +- modules/ui.py | 4 ++-- modules/upscaler.py | 2 +- 14 files changed, 16 insertions(+), 20 deletions(-) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index d906a571..e01ca655 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -1,6 +1,6 @@ import argparse import os -from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file # noqa: F401 parser = argparse.ArgumentParser() diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 122fce7f..1c4554a2 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -2,7 +2,6 @@ import os import re import torch -from PIL import Image import numpy as np from modules import modelloader, paths, deepbooru_model, devices, images, shared diff --git a/modules/extensions.py b/modules/extensions.py index 829f8cd9..bc2c0450 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -6,7 +6,7 @@ import time import git from modules import shared -from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path +from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 extensions = [] diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index fbe6215a..0131dea4 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -78,7 +78,7 @@ def setup_model(dirname): try: from gfpgan import GFPGANer - from facexlib import detection, parsing + from facexlib import detection, parsing # noqa: F401 global user_path global have_gfpgan global gfpgan_constructor diff --git a/modules/models/diffusion/uni_pc/__init__.py b/modules/models/diffusion/uni_pc/__init__.py index e1265e3f..dbb35964 100644 --- a/modules/models/diffusion/uni_pc/__init__.py +++ b/modules/models/diffusion/uni_pc/__init__.py @@ -1 +1 @@ -from .sampler import UniPCSampler +from .sampler import UniPCSampler # noqa: F401 diff --git a/modules/paths.py b/modules/paths.py index acf1894b..5f6474c0 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -1,8 +1,8 @@ import os import sys -from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir # noqa: F401 -import modules.safe +import modules.safe # noqa: F401 # data_path = cmd_opts_pre.data diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 9ec1adf2..c24d8dbb 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -17,9 +17,9 @@ class UpscalerRealESRGAN(Upscaler): self.user_path = path super().__init__() try: - from basicsr.archs.rrdbnet_arch import RRDBNet - from realesrgan import RealESRGANer - from realesrgan.archs.srvgg_arch import SRVGGNetCompact + from basicsr.archs.rrdbnet_arch import RRDBNet # noqa: F401 + from realesrgan import RealESRGANer # noqa: F401 + from realesrgan.archs.srvgg_arch import SRVGGNetCompact # noqa: F401 self.enable = True self.scalers = [] scalers = self.load_models(path) diff --git a/modules/script_loading.py b/modules/script_loading.py index a7d2203f..57b15862 100644 --- a/modules/script_loading.py +++ b/modules/script_loading.py @@ -2,7 +2,6 @@ import os import sys import traceback import importlib.util -from types import ModuleType def load_module(path): diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 344d75c8..058575b7 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -4,7 +4,7 @@ import ldm.models.diffusion.ddpm import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from ldm.models.diffusion.ddim import DDIMSampler, noise_like +from ldm.models.diffusion.ddim import noise_like from ldm.models.diffusion.sampling_util import norm_thresholding diff --git a/modules/sd_models.py b/modules/sd_models.py index 1c09c709..d1e946a5 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config -from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer @@ -87,8 +86,7 @@ class CheckpointInfo: try: # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start. - - from transformers import logging, CLIPModel + from transformers import logging, CLIPModel # noqa: F401 logging.set_verbosity_error() except Exception: diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index ff361f22..4f1bf21d 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -1,7 +1,7 @@ from modules import sd_samplers_compvis, sd_samplers_kdiffusion, shared # imports for functions that previously were here and are used by other modules -from modules.sd_samplers_common import samples_to_image_grid, sample_to_image +from modules.sd_samplers_common import samples_to_image_grid, sample_to_image # noqa: F401 all_samplers = [ *sd_samplers_kdiffusion.samplers_data_k_diffusion, diff --git a/modules/shared.py b/modules/shared.py index 44cd2c0c..7d70f041 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -12,7 +12,7 @@ import modules.memmon import modules.styles import modules.devices as devices from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args -from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 from ldm.models.diffusion.ddpm import LatentDiffusion demo = None diff --git a/modules/ui.py b/modules/ui.py index f7e57593..782b569d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -10,10 +10,10 @@ import gradio as gr import gradio.routes import gradio.utils import numpy as np -from PIL import Image, PngImagePlugin +from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call -from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress +from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path diff --git a/modules/upscaler.py b/modules/upscaler.py index 777593b0..e145be30 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -41,7 +41,7 @@ class Upscaler: os.makedirs(self.model_path, exist_ok=True) try: - import cv2 + import cv2 # noqa: F401 self.can_tile = True except Exception: pass -- cgit v1.2.3 From 028d3f6425d85f122027c127fba8bcbf4f66ee75 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:05:02 +0300 Subject: ruff auto fixes --- modules/config_states.py | 2 +- modules/deepbooru.py | 2 +- modules/devices.py | 2 +- modules/hypernetworks/hypernetwork.py | 2 +- modules/hypernetworks/ui.py | 4 ++-- modules/interrogate.py | 2 +- modules/modelloader.py | 2 +- modules/models/diffusion/ddpm_edit.py | 4 ++-- modules/scripts_auto_postprocessing.py | 2 +- modules/sd_hijack.py | 2 +- modules/sd_hijack_optimizations.py | 14 +++++++------- modules/sd_samplers_compvis.py | 2 +- modules/sd_samplers_kdiffusion.py | 2 +- modules/shared.py | 6 +++--- modules/textual_inversion/textual_inversion.py | 2 +- modules/ui.py | 8 ++++---- modules/ui_extra_networks.py | 4 ++-- modules/ui_tempdir.py | 2 +- 18 files changed, 32 insertions(+), 32 deletions(-) (limited to 'modules') diff --git a/modules/config_states.py b/modules/config_states.py index 8f1ff428..75da862a 100644 --- a/modules/config_states.py +++ b/modules/config_states.py @@ -35,7 +35,7 @@ def list_config_states(): j["filepath"] = path config_states.append(j) - config_states = list(sorted(config_states, key=lambda cs: cs["created_at"], reverse=True)) + config_states = sorted(config_states, key=lambda cs: cs["created_at"], reverse=True) for cs in config_states: timestamp = time.asctime(time.gmtime(cs["created_at"])) diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 1c4554a2..547e1b4c 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -78,7 +78,7 @@ class DeepDanbooru: res = [] - filtertags = set([x.strip().replace(' ', '_') for x in shared.opts.deepbooru_filter_tags.split(",")]) + filtertags = {x.strip().replace(' ', '_') for x in shared.opts.deepbooru_filter_tags.split(",")} for tag in [x for x in tags if x not in filtertags]: probability = probability_dict[tag] diff --git a/modules/devices.py b/modules/devices.py index c705a3cb..d8a34a0f 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -65,7 +65,7 @@ def enable_tf32(): # enabling benchmark option seems to enable a range of cards to do fp16 when they otherwise can't # see https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/4407 - if any([torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())]): + if any(torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())): torch.backends.cudnn.benchmark = True torch.backends.cuda.matmul.allow_tf32 = True diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 9fe749b7..6ef0bfdf 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -403,7 +403,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): k = self.to_k(context_k) v = self.to_v(context_v) - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v)) sim = einsum('b i d, b j d -> b i j', q, k) * self.scale diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index be168736..e3f9eb13 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -5,13 +5,13 @@ import modules.hypernetworks.hypernetwork from modules import devices, sd_hijack, shared not_available = ["hardswish", "multiheadattention"] -keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available) +keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available] def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None): filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure) - return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {filename}", "" + return gr.Dropdown.update(choices=sorted(shared.hypernetworks.keys())), f"Created: {filename}", "" def train_hypernetwork(*args): diff --git a/modules/interrogate.py b/modules/interrogate.py index 22df9216..a1c8e537 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -159,7 +159,7 @@ class InterrogateModels: text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)] top_count = min(top_count, len(text_array)) - text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(devices.device_interrogate) + text_tokens = clip.tokenize(list(text_array), truncate=True).to(devices.device_interrogate) text_features = self.clip_model.encode_text(text_tokens).type(self.dtype) text_features /= text_features.norm(dim=-1, keepdim=True) diff --git a/modules/modelloader.py b/modules/modelloader.py index 92ada694..25612bf8 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -39,7 +39,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None if os.path.islink(full_path) and not os.path.exists(full_path): print(f"Skipping broken symlink: {full_path}") continue - if ext_blacklist is not None and any([full_path.endswith(x) for x in ext_blacklist]): + if ext_blacklist is not None and any(full_path.endswith(x) for x in ext_blacklist): continue if full_path not in output: output.append(full_path) diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index 611c2b69..09432117 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -1130,7 +1130,7 @@ class LatentDiffusion(DDPM): if cond is not None: if isinstance(cond, dict): cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else - list(map(lambda x: x[:batch_size], cond[key])) for key in cond} + [x[:batch_size] for x in cond[key]] for key in cond} else: cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size] @@ -1229,7 +1229,7 @@ class LatentDiffusion(DDPM): if cond is not None: if isinstance(cond, dict): cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else - list(map(lambda x: x[:batch_size], cond[key])) for key in cond} + [x[:batch_size] for x in cond[key]] for key in cond} else: cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size] return self.p_sample_loop(cond, diff --git a/modules/scripts_auto_postprocessing.py b/modules/scripts_auto_postprocessing.py index 30d6d658..d63078de 100644 --- a/modules/scripts_auto_postprocessing.py +++ b/modules/scripts_auto_postprocessing.py @@ -17,7 +17,7 @@ class ScriptPostprocessingForMainUI(scripts.Script): return self.postprocessing_controls.values() def postprocess_image(self, p, script_pp, *args): - args_dict = {k: v for k, v in zip(self.postprocessing_controls, args)} + args_dict = dict(zip(self.postprocessing_controls, args)) pp = scripts_postprocessing.PostprocessedImage(script_pp.image) pp.info = {} diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 81573b78..e374aeb8 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -37,7 +37,7 @@ def apply_optimizations(): optimization_method = None - can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(getattr(torch.nn.functional, "scaled_dot_product_attention")) # not everyone has torch 2.x to use sdp + can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)): print("Applying xformers cross attention optimization.") diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index b623d53d..a174bbe1 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -49,7 +49,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None): v_in = self.to_v(context_v) del context, context_k, context_v, x - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in)) + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in)) del q_in, k_in, v_in dtype = q.dtype @@ -98,7 +98,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None): del context, x - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in)) + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in)) del q_in, k_in, v_in r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype) @@ -229,7 +229,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None): with devices.without_autocast(disable=not shared.opts.upcast_attn): k = k * self.scale - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v)) r = einsum_op(q, k, v) r = r.to(dtype) return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h)) @@ -334,7 +334,7 @@ def xformers_attention_forward(self, x, context=None, mask=None): k_in = self.to_k(context_k) v_in = self.to_v(context_v) - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in)) + q, k, v = (rearrange(t, 'b n (h d) -> b n h d', h=h) for t in (q_in, k_in, v_in)) del q_in, k_in, v_in dtype = q.dtype @@ -460,7 +460,7 @@ def xformers_attnblock_forward(self, x): k = self.k(h_) v = self.v(h_) b, c, h, w = q.shape - q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v)) + q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v)) dtype = q.dtype if shared.opts.upcast_attn: q, k = q.float(), k.float() @@ -482,7 +482,7 @@ def sdp_attnblock_forward(self, x): k = self.k(h_) v = self.v(h_) b, c, h, w = q.shape - q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v)) + q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v)) dtype = q.dtype if shared.opts.upcast_attn: q, k = q.float(), k.float() @@ -506,7 +506,7 @@ def sub_quad_attnblock_forward(self, x): k = self.k(h_) v = self.v(h_) b, c, h, w = q.shape - q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v)) + q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v)) q = q.contiguous() k = k.contiguous() v = v.contiguous() diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index bfcc5574..7427648f 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -83,7 +83,7 @@ class VanillaStableDiffusionSampler: conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step) unconditional_conditioning = prompt_parser.reconstruct_cond_batch(unconditional_conditioning, self.step) - assert all([len(conds) == 1 for conds in conds_list]), 'composition via AND is not supported for DDIM/PLMS samplers' + assert all(len(conds) == 1 for conds in conds_list), 'composition via AND is not supported for DDIM/PLMS samplers' cond = tensor # for DDIM, shapes must match, we can't just process cond and uncond independently; diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 3b8e9622..2f733cf5 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -86,7 +86,7 @@ class CFGDenoiser(torch.nn.Module): conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step) uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step) - assert not is_edit_model or all([len(conds) == 1 for conds in conds_list]), "AND is not supported for InstructPix2Pix checkpoint (unless using Image CFG scale = 1.0)" + assert not is_edit_model or all(len(conds) == 1 for conds in conds_list), "AND is not supported for InstructPix2Pix checkpoint (unless using Image CFG scale = 1.0)" batch_size = len(conds_list) repeats = [len(conds_list[i]) for i in range(batch_size)] diff --git a/modules/shared.py b/modules/shared.py index 7d70f041..e2691585 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(hypernetworks.keys())}, refresh=reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { @@ -403,7 +403,7 @@ options_templates.update(options_section(('ui', "User interface"), { "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}), - "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}), + "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}), "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"), "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"), "localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), @@ -583,7 +583,7 @@ class Options: if item.section not in section_ids: section_ids[item.section] = len(section_ids) - self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])} + self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) def cast_value(self, key, value): """casts an arbitrary to the same type as this setting's value with key diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 9ed9ba45..c37bb2ad 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -167,7 +167,7 @@ class EmbeddingDatabase: if 'string_to_param' in data: param_dict = data['string_to_param'] if hasattr(param_dict, '_parameters'): - param_dict = getattr(param_dict, '_parameters') # fix for torch 1.12.1 loading saved file from torch 1.11 + param_dict = param_dict._parameters # fix for torch 1.12.1 loading saved file from torch 1.11 assert len(param_dict) == 1, 'embedding file has multiple terms in it' emb = next(iter(param_dict.items()))[1] # diffuser concepts diff --git a/modules/ui.py b/modules/ui.py index 782b569d..84d661b2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1222,7 +1222,7 @@ def create_ui(): ) def get_textual_inversion_template_names(): - return sorted([x for x in textual_inversion.textual_inversion_templates]) + return sorted(textual_inversion.textual_inversion_templates) with gr.Tab(label="Train", id="train"): gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images [wiki]

") @@ -1230,8 +1230,8 @@ def create_ui(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") - train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()]) - create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name") + train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=list(shared.hypernetworks.keys())) + create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks.keys())}, "refresh_train_hypernetwork_name") with FormRow(): embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate") @@ -1808,7 +1808,7 @@ def create_ui(): if type(x) == gr.Dropdown: def check_dropdown(val): if getattr(x, 'multiselect', False): - return all([value in x.choices for value in val]) + return all(value in x.choices for value in val) else: return val in x.choices diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 800e467a..ab585917 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -26,7 +26,7 @@ def register_page(page): def fetch_file(filename: str = ""): from starlette.responses import FileResponse - if not any([Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs]): + if not any(Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs): raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.") ext = os.path.splitext(filename)[1].lower() @@ -326,7 +326,7 @@ def setup_ui(ui, gallery): is_allowed = False for extra_page in ui.stored_extra_pages: - if any([path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()]): + if any(path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()): is_allowed = True break diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py index 46fa9cb0..cac73c51 100644 --- a/modules/ui_tempdir.py +++ b/modules/ui_tempdir.py @@ -23,7 +23,7 @@ def register_tmp_file(gradio, filename): def check_tmp_file(gradio, filename): if hasattr(gradio, 'temp_file_sets'): - return any([filename in fileset for fileset in gradio.temp_file_sets]) + return any(filename in fileset for fileset in gradio.temp_file_sets) if hasattr(gradio, 'temp_dirs'): return any(Path(temp_dir).resolve() in Path(filename).resolve().parents for temp_dir in gradio.temp_dirs) -- cgit v1.2.3 From 550256db1ce18778a9d56ff343d844c61b9f9b83 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:19:16 +0300 Subject: ruff manual fixes --- modules/api/api.py | 18 ++++++++++++------ modules/codeformer/codeformer_arch.py | 7 +++++-- modules/codeformer/vqgan_arch.py | 4 ++-- modules/generation_parameters_copypaste.py | 4 ++-- modules/models/diffusion/ddpm_edit.py | 14 ++++++++------ modules/models/diffusion/uni_pc/uni_pc.py | 7 +++++-- modules/safe.py | 2 +- modules/sd_samplers_compvis.py | 2 +- modules/textual_inversion/image_embedding.py | 2 +- modules/textual_inversion/learn_schedule.py | 4 ++-- 10 files changed, 39 insertions(+), 25 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index f52d371b..9efb558e 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -34,14 +34,16 @@ import piexif.helper def upscaler_to_index(name: str): try: return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except Exception: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") + except Exception as e: + raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") from e + def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) - except Exception: - raise HTTPException(status_code=422, detail=f"Script '{name}' not found") + except Exception as e: + raise HTTPException(status_code=422, detail=f"Script '{name}' not found") from e + def validate_sampler_name(name): config = sd_samplers.all_samplers_map.get(name, None) @@ -50,20 +52,23 @@ def validate_sampler_name(name): return name + def setUpscalers(req: dict): reqDict = vars(req) reqDict['extras_upscaler_1'] = reqDict.pop('upscaler_1', None) reqDict['extras_upscaler_2'] = reqDict.pop('upscaler_2', None) return reqDict + def decode_base64_to_image(encoding): if encoding.startswith("data:image/"): encoding = encoding.split(";")[1].split(",")[1] try: image = Image.open(BytesIO(base64.b64decode(encoding))) return image - except Exception: - raise HTTPException(status_code=500, detail="Invalid encoded image") + except Exception as e: + raise HTTPException(status_code=500, detail="Invalid encoded image") from e + def encode_pil_to_base64(image): with io.BytesIO() as output_bytes: @@ -94,6 +99,7 @@ def encode_pil_to_base64(image): return base64.b64encode(bytes_data) + def api_middleware(app: FastAPI): rich_available = True try: diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 00c407de..ff1c0b4b 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -161,10 +161,13 @@ class Fuse_sft_block(nn.Module): class CodeFormer(VQAutoEncoder): def __init__(self, dim_embd=512, n_head=8, n_layers=9, codebook_size=1024, latent_size=256, - connect_list=['32', '64', '128', '256'], - fix_modules=['quantize','generator']): + connect_list=None, + fix_modules=None): super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size) + connect_list = connect_list or ['32', '64', '128', '256'] + fix_modules = fix_modules or ['quantize', 'generator'] + if fix_modules is not None: for module in fix_modules: for param in getattr(self, module).parameters(): diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index 820e6b12..b24a0394 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -326,7 +326,7 @@ class Generator(nn.Module): @ARCH_REGISTRY.register() class VQAutoEncoder(nn.Module): - def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=[16], codebook_size=1024, emb_dim=256, + def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=None, codebook_size=1024, emb_dim=256, beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None): super().__init__() logger = get_root_logger() @@ -337,7 +337,7 @@ class VQAutoEncoder(nn.Module): self.embed_dim = emb_dim self.ch_mult = ch_mult self.resolution = img_size - self.attn_resolutions = attn_resolutions + self.attn_resolutions = attn_resolutions or [16] self.quantizer_type = quantizer self.encoder = Encoder( self.in_channels, diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index f1c59c46..7fbbe707 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -19,14 +19,14 @@ registered_param_bindings = [] class ParamBinding: - def __init__(self, paste_button, tabname, source_text_component=None, source_image_component=None, source_tabname=None, override_settings_component=None, paste_field_names=[]): + def __init__(self, paste_button, tabname, source_text_component=None, source_image_component=None, source_tabname=None, override_settings_component=None, paste_field_names=None): self.paste_button = paste_button self.tabname = tabname self.source_text_component = source_text_component self.source_image_component = source_image_component self.source_tabname = source_tabname self.override_settings_component = override_settings_component - self.paste_field_names = paste_field_names + self.paste_field_names = paste_field_names or [] def reset(): diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index 09432117..af4dea15 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -52,7 +52,7 @@ class DDPM(pl.LightningModule): beta_schedule="linear", loss_type="l2", ckpt_path=None, - ignore_keys=[], + ignore_keys=None, load_only_unet=False, monitor="val/loss", use_ema=True, @@ -107,7 +107,7 @@ class DDPM(pl.LightningModule): print(f"Keeping EMAs of {len(list(self.model_ema.buffers()))}.") if ckpt_path is not None: - self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys, only_model=load_only_unet) + self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys or [], only_model=load_only_unet) # If initialing from EMA-only checkpoint, create EMA model after loading. if self.use_ema and not load_ema: @@ -194,7 +194,9 @@ class DDPM(pl.LightningModule): if context is not None: print(f"{context}: Restored training weights") - def init_from_ckpt(self, path, ignore_keys=list(), only_model=False): + def init_from_ckpt(self, path, ignore_keys=None, only_model=False): + ignore_keys = ignore_keys or [] + sd = torch.load(path, map_location="cpu") if "state_dict" in list(sd.keys()): sd = sd["state_dict"] @@ -473,7 +475,7 @@ class LatentDiffusion(DDPM): conditioning_key = None ckpt_path = kwargs.pop("ckpt_path", None) ignore_keys = kwargs.pop("ignore_keys", []) - super().__init__(conditioning_key=conditioning_key, *args, load_ema=load_ema, **kwargs) + super().__init__(*args, conditioning_key=conditioning_key, load_ema=load_ema, **kwargs) self.concat_mode = concat_mode self.cond_stage_trainable = cond_stage_trainable self.cond_stage_key = cond_stage_key @@ -1433,10 +1435,10 @@ class Layout2ImgDiffusion(LatentDiffusion): # TODO: move all layout-specific hacks to this class def __init__(self, cond_stage_key, *args, **kwargs): assert cond_stage_key == 'coordinates_bbox', 'Layout2ImgDiffusion only for cond_stage_key="coordinates_bbox"' - super().__init__(cond_stage_key=cond_stage_key, *args, **kwargs) + super().__init__(*args, cond_stage_key=cond_stage_key, **kwargs) def log_images(self, batch, N=8, *args, **kwargs): - logs = super().log_images(batch=batch, N=N, *args, **kwargs) + logs = super().log_images(*args, batch=batch, N=N, **kwargs) key = 'train' if self.training else 'validation' dset = self.trainer.datamodule.datasets[key] diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index a4c4ef4e..6f8ad631 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -178,13 +178,13 @@ def model_wrapper( model, noise_schedule, model_type="noise", - model_kwargs={}, + model_kwargs=None, guidance_type="uncond", #condition=None, #unconditional_condition=None, guidance_scale=1., classifier_fn=None, - classifier_kwargs={}, + classifier_kwargs=None, ): """Create a wrapper function for the noise prediction model. @@ -275,6 +275,9 @@ def model_wrapper( A noise prediction model that accepts the noised data and the continuous time as the inputs. """ + model_kwargs = model_kwargs or [] + classifier_kwargs = classifier_kwargs or [] + def get_model_input_time(t_continuous): """ Convert the continuous-time `t_continuous` (in [epsilon, T]) to the model input time. diff --git a/modules/safe.py b/modules/safe.py index e6c2f2c0..2d5b972f 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -104,7 +104,7 @@ def check_pt(filename, extra_handler): def load(filename, *args, **kwargs): - return load_with_extra(filename, extra_handler=global_extra_handler, *args, **kwargs) + return load_with_extra(filename, *args, extra_handler=global_extra_handler, **kwargs) def load_with_extra(filename, extra_handler=None, *args, **kwargs): diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 7427648f..b1ee3be7 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -55,7 +55,7 @@ class VanillaStableDiffusionSampler: def p_sample_ddim_hook(self, x_dec, cond, ts, unconditional_conditioning, *args, **kwargs): x_dec, ts, cond, unconditional_conditioning = self.before_sample(x_dec, ts, cond, unconditional_conditioning) - res = self.orig_p_sample_ddim(x_dec, cond, ts, unconditional_conditioning=unconditional_conditioning, *args, **kwargs) + res = self.orig_p_sample_ddim(x_dec, cond, ts, *args, unconditional_conditioning=unconditional_conditioning, **kwargs) x_dec, ts, cond, unconditional_conditioning, res = self.after_sample(x_dec, ts, cond, unconditional_conditioning, res) diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py index ee0e850a..d85a4888 100644 --- a/modules/textual_inversion/image_embedding.py +++ b/modules/textual_inversion/image_embedding.py @@ -17,7 +17,7 @@ class EmbeddingEncoder(json.JSONEncoder): class EmbeddingDecoder(json.JSONDecoder): def __init__(self, *args, **kwargs): - json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs) + json.JSONDecoder.__init__(self, *args, object_hook=self.object_hook, **kwargs) def object_hook(self, d): if 'TORCHTENSOR' in d: diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index f63fc72f..fda58898 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -32,8 +32,8 @@ class LearnScheduleIterator: self.maxit += 1 return assert self.rates - except (ValueError, AssertionError): - raise Exception('Invalid learning rate schedule. It should be a number or, for example, like "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000.') + except (ValueError, AssertionError) as e: + raise Exception('Invalid learning rate schedule. It should be a number or, for example, like "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000.') from e def __iter__(self): -- cgit v1.2.3 From a5121e7a0623db328a9462d340d389ed6737374a Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:37:18 +0300 Subject: fixes for B007 --- modules/codeformer_model.py | 2 +- modules/esrgan_model.py | 8 ++------ modules/extra_networks.py | 2 +- modules/generation_parameters_copypaste.py | 2 +- modules/hypernetworks/hypernetwork.py | 12 ++++++------ modules/images.py | 2 +- modules/interrogate.py | 4 ++-- modules/prompt_parser.py | 14 +++++++------- modules/safe.py | 4 ++-- modules/scripts.py | 10 +++++----- modules/scripts_postprocessing.py | 8 ++++---- modules/sd_hijack_clip.py | 2 +- modules/shared.py | 6 +++--- modules/textual_inversion/learn_schedule.py | 2 +- modules/textual_inversion/textual_inversion.py | 10 +++++----- modules/ui.py | 6 +++--- modules/ui_extra_networks.py | 2 +- modules/ui_tempdir.py | 2 +- modules/upscaler.py | 2 +- 19 files changed, 48 insertions(+), 52 deletions(-) (limited to 'modules') diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 8e56cb89..ececdbae 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -94,7 +94,7 @@ def setup_model(dirname): self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5) self.face_helper.align_warp_face() - for idx, cropped_face in enumerate(self.face_helper.cropped_faces): + for cropped_face in self.face_helper.cropped_faces: cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True) normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True) cropped_face_t = cropped_face_t.unsqueeze(0).to(devices.device_codeformer) diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 85aa6934..a009eb42 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -16,9 +16,7 @@ def mod2normal(state_dict): # this code is copied from https://github.com/victorca25/iNNfer if 'conv_first.weight' in state_dict: crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] @@ -52,9 +50,7 @@ def resrgan2normal(state_dict, nb=23): if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict: re8x = 0 crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] diff --git a/modules/extra_networks.py b/modules/extra_networks.py index 1978673d..f9db41bc 100644 --- a/modules/extra_networks.py +++ b/modules/extra_networks.py @@ -91,7 +91,7 @@ def deactivate(p, extra_network_data): """call deactivate for extra networks in extra_network_data in specified order, then call deactivate for all remaining registered networks""" - for extra_network_name, extra_network_args in extra_network_data.items(): + for extra_network_name in extra_network_data: extra_network = extra_network_registry.get(extra_network_name, None) if extra_network is None: continue diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 7fbbe707..b0e945a1 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -247,7 +247,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model lines.append(lastline) lastline = '' - for i, line in enumerate(lines): + for line in lines: line = line.strip() if line.startswith("Negative prompt:"): done_with_prompt = True diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 6ef0bfdf..38ef074f 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -177,34 +177,34 @@ class Hypernetwork: def weights(self): res = [] - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: res += layer.parameters() return res def train(self, mode=True): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.train(mode=mode) for param in layer.parameters(): param.requires_grad = mode def to(self, device): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.to(device) return self def set_multiplier(self, multiplier): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.multiplier = multiplier return self def eval(self): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.eval() for param in layer.parameters(): @@ -619,7 +619,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/images.py b/modules/images.py index 7392cb8b..c4e98c75 100644 --- a/modules/images.py +++ b/modules/images.py @@ -149,7 +149,7 @@ def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0): return ImageFont.truetype(Roboto, fontsize) def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize): - for i, line in enumerate(lines): + for line in lines: fnt = initial_fnt fontsize = initial_fontsize while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0: diff --git a/modules/interrogate.py b/modules/interrogate.py index a1c8e537..111b1322 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -207,8 +207,8 @@ class InterrogateModels: image_features /= image_features.norm(dim=-1, keepdim=True) - for name, topn, items in self.categories(): - matches = self.rank(image_features, items, top_count=topn) + for cat in self.categories(): + matches = self.rank(image_features, cat.items, top_count=cat.topn) for match, score in matches: if shared.opts.interrogate_return_ranks: res += f", ({match}:{score/100:.3f})" diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index 3a720721..b4aff704 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -143,7 +143,7 @@ def get_learned_conditioning(model, prompts, steps): conds = model.get_learned_conditioning(texts) cond_schedule = [] - for i, (end_at_step, text) in enumerate(prompt_schedule): + for i, (end_at_step, _) in enumerate(prompt_schedule): cond_schedule.append(ScheduledPromptConditioning(end_at_step, conds[i])) cache[prompt] = cond_schedule @@ -219,8 +219,8 @@ def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_s res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype) for i, cond_schedule in enumerate(c): target_index = 0 - for current, (end_at, cond) in enumerate(cond_schedule): - if current_step <= end_at: + for current, entry in enumerate(cond_schedule): + if current_step <= entry.end_at_step: target_index = current break res[i] = cond_schedule[target_index].cond @@ -234,13 +234,13 @@ def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step): tensors = [] conds_list = [] - for batch_no, composable_prompts in enumerate(c.batch): + for composable_prompts in c.batch: conds_for_batch = [] - for cond_index, composable_prompt in enumerate(composable_prompts): + for composable_prompt in composable_prompts: target_index = 0 - for current, (end_at, cond) in enumerate(composable_prompt.schedules): - if current_step <= end_at: + for current, entry in enumerate(composable_prompt.schedules): + if current_step <= entry.end_at_step: target_index = current break diff --git a/modules/safe.py b/modules/safe.py index 2d5b972f..1e791c5b 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -95,11 +95,11 @@ def check_pt(filename, extra_handler): except zipfile.BadZipfile: - # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle + # if it's not a zip file, it's an old pytorch format, with five objects written to pickle with open(filename, "rb") as file: unpickler = RestrictedUnpickler(file) unpickler.extra_handler = extra_handler - for i in range(5): + for _ in range(5): unpickler.load() diff --git a/modules/scripts.py b/modules/scripts.py index d945b89f..0c12ebd5 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -231,7 +231,7 @@ def load_scripts(): syspath = sys.path def register_scripts_from_module(module): - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) != type: continue @@ -295,9 +295,9 @@ class ScriptRunner: auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data() - for script_class, path, basedir, script_module in auto_processing_scripts + scripts_data: - script = script_class() - script.filename = path + for script_data in auto_processing_scripts + scripts_data: + script = script_data.script_class() + script.filename = script_data.path script.is_txt2img = not is_img2img script.is_img2img = is_img2img @@ -492,7 +492,7 @@ class ScriptRunner: module = script_loading.load_module(script.filename) cache[filename] = module - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) == type and issubclass(script_class, Script): self.scripts[si] = script_class() self.scripts[si].filename = filename diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py index b11568c0..6751406c 100644 --- a/modules/scripts_postprocessing.py +++ b/modules/scripts_postprocessing.py @@ -66,9 +66,9 @@ class ScriptPostprocessingRunner: def initialize_scripts(self, scripts_data): self.scripts = [] - for script_class, path, basedir, script_module in scripts_data: - script: ScriptPostprocessing = script_class() - script.filename = path + for script_data in scripts_data: + script: ScriptPostprocessing = script_data.script_class() + script.filename = script_data.path if script.name == "Simple Upscale": continue @@ -124,7 +124,7 @@ class ScriptPostprocessingRunner: script_args = args[script.args_from:script.args_to] process_args = {} - for (name, component), value in zip(script.controls.items(), script_args): + for (name, component), value in zip(script.controls.items(), script_args): # noqa B007 process_args[name] = value script.process(pp, **process_args) diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index 9fa5c5c5..c0c350f6 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): self.hijack.fixes = [x.fixes for x in batch_chunk] for fixes in self.hijack.fixes: - for position, embedding in fixes: + for position, embedding in fixes: # noqa: B007 used_embeddings[embedding.name] = embedding z = self.process_tokens(tokens, multipliers) diff --git a/modules/shared.py b/modules/shared.py index e2691585..913c9e63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -211,7 +211,7 @@ class OptionInfo: def options_section(section_identifier, options_dict): - for k, v in options_dict.items(): + for v in options_dict.values(): v.section = section_identifier return options_dict @@ -579,7 +579,7 @@ class Options: section_ids = {} settings_items = self.data_labels.items() - for k, item in settings_items: + for _, item in settings_items: if item.section not in section_ids: section_ids[item.section] = len(section_ids) @@ -740,7 +740,7 @@ def walk_files(path, allowed_extensions=None): if allowed_extensions is not None: allowed_extensions = set(allowed_extensions) - for root, dirs, files in os.walk(path): + for root, _, files in os.walk(path): for filename in files: if allowed_extensions is not None: _, ext = os.path.splitext(filename) diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index fda58898..c56bea45 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -12,7 +12,7 @@ class LearnScheduleIterator: self.it = 0 self.maxit = 0 try: - for i, pair in enumerate(pairs): + for pair in pairs: if not pair.strip(): continue tmp = pair.split(':') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index c37bb2ad..47035332 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -29,7 +29,7 @@ textual_inversion_templates = {} def list_textual_inversion_templates(): textual_inversion_templates.clear() - for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): + for root, _, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): for fn in fns: path = os.path.join(root, fn) @@ -198,7 +198,7 @@ class EmbeddingDatabase: if not os.path.isdir(embdir.path): return - for root, dirs, fns in os.walk(embdir.path, followlinks=True): + for root, _, fns in os.walk(embdir.path, followlinks=True): for fn in fns: try: fullfn = os.path.join(root, fn) @@ -215,7 +215,7 @@ class EmbeddingDatabase: def load_textual_inversion_embeddings(self, force_reload=False): if not force_reload: need_reload = False - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): if embdir.has_changed(): need_reload = True break @@ -228,7 +228,7 @@ class EmbeddingDatabase: self.skipped_embeddings.clear() self.expected_shape = self.get_expected_shape() - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): self.load_from_dir(embdir) embdir.update() @@ -469,7 +469,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/ui.py b/modules/ui.py index 84d661b2..83bfb7d8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -416,7 +416,7 @@ def create_sampler_and_steps_selection(choices, tabname): def ordered_ui_categories(): user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))} - for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): + for _, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): yield category @@ -1646,7 +1646,7 @@ def create_ui(): with gr.Blocks(theme=shared.gradio_theme, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings", variant="compact"): - for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): + for _i, k, _item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): component = create_setting_component(k, is_quicksettings=True) component_dict[k] = component @@ -1673,7 +1673,7 @@ def create_ui(): outputs=[text_settings, result], ) - for i, k, item in quicksettings_list: + for _i, k, _item in quicksettings_list: component = component_dict[k] info = opts.data_labels[k] diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index ab585917..2fd82e8e 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -90,7 +90,7 @@ class ExtraNetworksPage: subdirs = {} for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]: - for root, dirs, files in os.walk(parentdir): + for root, dirs, _ in os.walk(parentdir): for dirname in dirs: x = os.path.join(root, dirname) diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py index cac73c51..f05049e1 100644 --- a/modules/ui_tempdir.py +++ b/modules/ui_tempdir.py @@ -72,7 +72,7 @@ def cleanup_tmpdr(): if temp_dir == "" or not os.path.isdir(temp_dir): return - for root, dirs, files in os.walk(temp_dir, topdown=False): + for root, _, files in os.walk(temp_dir, topdown=False): for name in files: _, extension = os.path.splitext(name) if extension != ".png": diff --git a/modules/upscaler.py b/modules/upscaler.py index e145be30..8acb6e96 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -55,7 +55,7 @@ class Upscaler: dest_w = int(img.width * scale) dest_h = int(img.height * scale) - for i in range(3): + for _ in range(3): shape = (img.width, img.height) img = self.do_upscale(img, selected_model) -- cgit v1.2.3 From d25219b7e889cf34bccae9cb88497708796efda2 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:55:09 +0300 Subject: manual fixes for some C408 --- modules/api/api.py | 2 +- modules/models/diffusion/ddpm_edit.py | 8 ++++---- modules/models/diffusion/uni_pc/uni_pc.py | 4 ++-- modules/sd_hijack_inpainting.py | 2 +- 4 files changed, 8 insertions(+), 8 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index 9efb558e..594fa655 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -165,7 +165,7 @@ def api_middleware(app: FastAPI): class Api: def __init__(self, app: FastAPI, queue_lock: Lock): if shared.cmd_opts.api_auth: - self.credentials = dict() + self.credentials = {} for auth in shared.cmd_opts.api_auth.split(","): user, password = auth.split(":") self.credentials[user] = password diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index af4dea15..3fb76b65 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -405,7 +405,7 @@ class DDPM(pl.LightningModule): @torch.no_grad() def log_images(self, batch, N=8, n_row=2, sample=True, return_keys=None, **kwargs): - log = dict() + log = {} x = self.get_input(batch, self.first_stage_key) N = min(x.shape[0], N) n_row = min(x.shape[0], n_row) @@ -413,7 +413,7 @@ class DDPM(pl.LightningModule): log["inputs"] = x # get diffusion row - diffusion_row = list() + diffusion_row = [] x_start = x[:n_row] for t in range(self.num_timesteps): @@ -1263,7 +1263,7 @@ class LatentDiffusion(DDPM): use_ddim = False - log = dict() + log = {} z, c, x, xrec, xc = self.get_input(batch, self.first_stage_key, return_first_stage_outputs=True, force_c_encode=True, @@ -1291,7 +1291,7 @@ class LatentDiffusion(DDPM): if plot_diffusion_rows: # get diffusion row - diffusion_row = list() + diffusion_row = [] z_start = z[:n_row] for t in range(self.num_timesteps): if t % self.log_every_t == 0 or t == self.num_timesteps - 1: diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index 6f8ad631..f6c49f87 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -344,7 +344,7 @@ def model_wrapper( t_in = torch.cat([t_continuous] * 2) if isinstance(condition, dict): assert isinstance(unconditional_condition, dict) - c_in = dict() + c_in = {} for k in condition: if isinstance(condition[k], list): c_in[k] = [torch.cat([ @@ -355,7 +355,7 @@ def model_wrapper( unconditional_condition[k], condition[k]]) elif isinstance(condition, list): - c_in = list() + c_in = [] assert isinstance(unconditional_condition, list) for i in range(len(condition)): c_in.append(torch.cat([unconditional_condition[i], condition[i]])) diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 058575b7..c1977b19 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -23,7 +23,7 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F if isinstance(c, dict): assert isinstance(unconditional_conditioning, dict) - c_in = dict() + c_in = {} for k in c: if isinstance(c[k], list): c_in[k] = [ -- cgit v1.2.3 From 3ec7b705c78b7aca9569c92a419837352c7a4ec6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 21:21:32 +0300 Subject: suggestions and fixes from the PR --- modules/codeformer/codeformer_arch.py | 7 ++----- modules/hypernetworks/ui.py | 4 ++-- modules/models/diffusion/uni_pc/uni_pc.py | 4 ++-- modules/scripts_postprocessing.py | 2 +- modules/sd_hijack_clip.py | 2 +- modules/shared.py | 2 +- modules/textual_inversion/textual_inversion.py | 3 +-- modules/ui.py | 4 ++-- 8 files changed, 12 insertions(+), 16 deletions(-) (limited to 'modules') diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index ff1c0b4b..45c70f84 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -161,13 +161,10 @@ class Fuse_sft_block(nn.Module): class CodeFormer(VQAutoEncoder): def __init__(self, dim_embd=512, n_head=8, n_layers=9, codebook_size=1024, latent_size=256, - connect_list=None, - fix_modules=None): + connect_list=('32', '64', '128', '256'), + fix_modules=('quantize', 'generator')): super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size) - connect_list = connect_list or ['32', '64', '128', '256'] - fix_modules = fix_modules or ['quantize', 'generator'] - if fix_modules is not None: for module in fix_modules: for param in getattr(self, module).parameters(): diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index e3f9eb13..8b6255e2 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -5,13 +5,13 @@ import modules.hypernetworks.hypernetwork from modules import devices, sd_hijack, shared not_available = ["hardswish", "multiheadattention"] -keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available] +keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict if x not in not_available] def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None): filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure) - return gr.Dropdown.update(choices=sorted(shared.hypernetworks.keys())), f"Created: {filename}", "" + return gr.Dropdown.update(choices=sorted(shared.hypernetworks)), f"Created: {filename}", "" def train_hypernetwork(*args): diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index f6c49f87..a227b947 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -275,8 +275,8 @@ def model_wrapper( A noise prediction model that accepts the noised data and the continuous time as the inputs. """ - model_kwargs = model_kwargs or [] - classifier_kwargs = classifier_kwargs or [] + model_kwargs = model_kwargs or {} + classifier_kwargs = classifier_kwargs or {} def get_model_input_time(t_continuous): """ diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py index 6751406c..bac1335d 100644 --- a/modules/scripts_postprocessing.py +++ b/modules/scripts_postprocessing.py @@ -124,7 +124,7 @@ class ScriptPostprocessingRunner: script_args = args[script.args_from:script.args_to] process_args = {} - for (name, component), value in zip(script.controls.items(), script_args): # noqa B007 + for (name, _component), value in zip(script.controls.items(), script_args): process_args[name] = value script.process(pp, **process_args) diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index c0c350f6..cc6e8c21 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): self.hijack.fixes = [x.fixes for x in batch_chunk] for fixes in self.hijack.fixes: - for position, embedding in fixes: # noqa: B007 + for _position, embedding in fixes: used_embeddings[embedding.name] = embedding z = self.process_tokens(tokens, multipliers) diff --git a/modules/shared.py b/modules/shared.py index 913c9e63..ac67adc0 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(hypernetworks.keys())}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", hypernetworks]}, refresh=reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 47035332..9e1b2b9a 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -166,8 +166,7 @@ class EmbeddingDatabase: # textual inversion embeddings if 'string_to_param' in data: param_dict = data['string_to_param'] - if hasattr(param_dict, '_parameters'): - param_dict = param_dict._parameters # fix for torch 1.12.1 loading saved file from torch 1.11 + param_dict = getattr(param_dict, '_parameters', param_dict) # fix for torch 1.12.1 loading saved file from torch 1.11 assert len(param_dict) == 1, 'embedding file has multiple terms in it' emb = next(iter(param_dict.items()))[1] # diffuser concepts diff --git a/modules/ui.py b/modules/ui.py index 83bfb7d8..7ee99473 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1230,8 +1230,8 @@ def create_ui(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") - train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=list(shared.hypernetworks.keys())) - create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks.keys())}, "refresh_train_hypernetwork_name") + train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=sorted(shared.hypernetworks)) + create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks)}, "refresh_train_hypernetwork_name") with FormRow(): embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate") -- cgit v1.2.3 From 8aa87c564a79965013715d56a5f90d2a34d5d6ee Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 23:41:08 +0300 Subject: add UI to edit defaults allow setting defaults for elements in extensions' tabs fix a problem with ESRGAN upscalers disappearing after UI reload implicit change: HTML element id for train tab from tab_ti to tab_train (will this break things?) --- modules/modelloader.py | 27 +++---- modules/ui.py | 122 +++++------------------------ modules/ui_loadsave.py | 208 +++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 237 insertions(+), 120 deletions(-) create mode 100644 modules/ui_loadsave.py (limited to 'modules') diff --git a/modules/modelloader.py b/modules/modelloader.py index 25612bf8..2a479bcb 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -116,20 +116,6 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None): pass -builtin_upscaler_classes = [] -forbidden_upscaler_classes = set() - - -def list_builtin_upscalers(): - builtin_upscaler_classes.clear() - builtin_upscaler_classes.extend(Upscaler.__subclasses__()) - -def forbid_loaded_nonbuiltin_upscalers(): - for cls in Upscaler.__subclasses__(): - if cls not in builtin_upscaler_classes: - forbidden_upscaler_classes.add(cls) - - def load_upscalers(): # We can only do this 'magic' method to dynamically load upscalers if they are referenced, # so we'll try to import any _model.py files before looking in __subclasses__ @@ -145,10 +131,17 @@ def load_upscalers(): datas = [] commandline_options = vars(shared.cmd_opts) - for cls in Upscaler.__subclasses__(): - if cls in forbidden_upscaler_classes: - continue + # some of upscaler classes will not go away after reloading their modules, and we'll end + # up with two copies of those classes. The newest copy will always be the last in the list, + # so we go from end to beginning and ignore duplicates + used_classes = {} + for cls in reversed(Upscaler.__subclasses__()): + classname = str(cls) + if classname not in used_classes: + used_classes[classname] = cls + + for cls in reversed(used_classes.values()): name = cls.__name__ cmd_name = f"{name.lower().replace('upscaler', '')}_models_path" scaler = cls(commandline_options.get(cmd_name, None)) diff --git a/modules/ui.py b/modules/ui.py index 7ee99473..1efb656a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -13,7 +13,7 @@ import numpy as np from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call -from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress +from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path @@ -86,16 +86,6 @@ def send_gradio_gallery_to_image(x): return None return image_from_url_text(x[0]) -def visit(x, func, path=""): - if hasattr(x, 'children'): - if isinstance(x, gr.Tabs) and x.elem_id is not None: - # Tabs element can't have a label, have to use elem_id instead - func(f"{path}/Tabs@{x.elem_id}", x) - for c in x.children: - visit(c, func, path) - elif x.label is not None: - func(f"{path}/{x.label}", x) - def add_style(name: str, prompt: str, negative_prompt: str): if name is None: @@ -1471,6 +1461,8 @@ def create_ui(): return res + loadsave = ui_loadsave.UiLoadsave(cmd_opts.ui_config_file) + components = [] component_dict = {} shared.settings_components = component_dict @@ -1558,6 +1550,9 @@ def create_ui(): current_row.__exit__() current_tab.__exit__() + with gr.TabItem("Defaults", id="defaults", elem_id="settings_tab_defaults"): + loadsave.create_ui() + with gr.TabItem("Actions", id="actions", elem_id="settings_tab_actions"): request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications") download_localization = gr.Button(value='Download localization template', elem_id="download_localization") @@ -1631,7 +1626,7 @@ def create_ui(): (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), - (train_interface, "Train", "ti"), + (train_interface, "Train", "train"), ] interfaces += script_callbacks.ui_tabs_callback() @@ -1659,6 +1654,16 @@ def create_ui(): with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"): interface.render() + for interface, _label, ifid in interfaces: + if ifid in ["extensions", "settings"]: + continue + + loadsave.add_block(interface, ifid) + + loadsave.add_component(f"webui/Tabs@{tabs.elem_id}", tabs) + + loadsave.setup_ui() + if os.path.exists(os.path.join(script_path, "notification.mp3")): gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) @@ -1747,97 +1752,8 @@ def create_ui(): ] ) - ui_config_file = cmd_opts.ui_config_file - ui_settings = {} - settings_count = len(ui_settings) - error_loading = False - - try: - if os.path.exists(ui_config_file): - with open(ui_config_file, "r", encoding="utf8") as file: - ui_settings = json.load(file) - except Exception: - error_loading = True - print("Error loading settings:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - - def loadsave(path, x): - def apply_field(obj, field, condition=None, init_field=None): - key = f"{path}/{field}" - - if getattr(obj, 'custom_script_source', None) is not None: - key = f"customscript/{obj.custom_script_source}/{key}" - - if getattr(obj, 'do_not_save_to_config', False): - return - - saved_value = ui_settings.get(key, None) - if saved_value is None: - ui_settings[key] = getattr(obj, field) - elif condition and not condition(saved_value): - pass - - # this warning is generally not useful; - # print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') - else: - setattr(obj, field, saved_value) - if init_field is not None: - init_field(saved_value) - - if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton] and x.visible: - apply_field(x, 'visible') - - if type(x) == gr.Slider: - apply_field(x, 'value') - apply_field(x, 'minimum') - apply_field(x, 'maximum') - apply_field(x, 'step') - - if type(x) == gr.Radio: - apply_field(x, 'value', lambda val: val in x.choices) - - if type(x) == gr.Checkbox: - apply_field(x, 'value') - - if type(x) == gr.Textbox: - apply_field(x, 'value') - - if type(x) == gr.Number: - apply_field(x, 'value') - - if type(x) == gr.Dropdown: - def check_dropdown(val): - if getattr(x, 'multiselect', False): - return all(value in x.choices for value in val) - else: - return val in x.choices - - apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None)) - - def check_tab_id(tab_id): - tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children)) - if type(tab_id) == str: - tab_ids = [t.id for t in tab_items] - return tab_id in tab_ids - elif type(tab_id) == int: - return tab_id >= 0 and tab_id < len(tab_items) - else: - return False - - if type(x) == gr.Tabs: - apply_field(x, 'selected', check_tab_id) - - visit(txt2img_interface, loadsave, "txt2img") - visit(img2img_interface, loadsave, "img2img") - visit(extras_interface, loadsave, "extras") - visit(modelmerger_interface, loadsave, "modelmerger") - visit(train_interface, loadsave, "train") - - loadsave(f"webui/Tabs@{tabs.elem_id}", tabs) - - if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)): - with open(ui_config_file, "w", encoding="utf8") as file: - json.dump(ui_settings, file, indent=4) + loadsave.dump_defaults() + demo.ui_loadsave = loadsave # Required as a workaround for change() event not triggering when loading values from ui-config.json interp_description.value = update_interp_description(interp_method.value) diff --git a/modules/ui_loadsave.py b/modules/ui_loadsave.py new file mode 100644 index 00000000..728fec9e --- /dev/null +++ b/modules/ui_loadsave.py @@ -0,0 +1,208 @@ +import json +import os + +import gradio as gr + +from modules import errors +from modules.ui_components import ToolButton + + +class UiLoadsave: + """allows saving and restorig default values for gradio components""" + + def __init__(self, filename): + self.filename = filename + self.ui_settings = {} + self.component_mapping = {} + self.error_loading = False + self.finalized_ui = False + + self.ui_defaults_view = None + self.ui_defaults_apply = None + self.ui_defaults_review = None + + try: + if os.path.exists(self.filename): + self.ui_settings = self.read_from_file() + except Exception as e: + self.error_loading = True + errors.display(e, "loading settings") + + def add_component(self, path, x): + """adds component to the registry of tracked components""" + + assert not self.finalized_ui + + def apply_field(obj, field, condition=None, init_field=None): + key = f"{path}/{field}" + + if getattr(obj, 'custom_script_source', None) is not None: + key = f"customscript/{obj.custom_script_source}/{key}" + + if getattr(obj, 'do_not_save_to_config', False): + return + + saved_value = self.ui_settings.get(key, None) + if saved_value is None: + self.ui_settings[key] = getattr(obj, field) + elif condition and not condition(saved_value): + pass + else: + setattr(obj, field, saved_value) + if init_field is not None: + init_field(saved_value) + + if field == 'value' and key not in self.component_mapping: + self.component_mapping[key] = x + + if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton] and x.visible: + apply_field(x, 'visible') + + if type(x) == gr.Slider: + apply_field(x, 'value') + apply_field(x, 'minimum') + apply_field(x, 'maximum') + apply_field(x, 'step') + + if type(x) == gr.Radio: + apply_field(x, 'value', lambda val: val in x.choices) + + if type(x) == gr.Checkbox: + apply_field(x, 'value') + + if type(x) == gr.Textbox: + apply_field(x, 'value') + + if type(x) == gr.Number: + apply_field(x, 'value') + + if type(x) == gr.Dropdown: + def check_dropdown(val): + if getattr(x, 'multiselect', False): + return all(value in x.choices for value in val) + else: + return val in x.choices + + apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None)) + + def check_tab_id(tab_id): + tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children)) + if type(tab_id) == str: + tab_ids = [t.id for t in tab_items] + return tab_id in tab_ids + elif type(tab_id) == int: + return 0 <= tab_id < len(tab_items) + else: + return False + + if type(x) == gr.Tabs: + apply_field(x, 'selected', check_tab_id) + + def add_block(self, x, path=""): + """adds all components inside a gradio block x to the registry of tracked components""" + + if hasattr(x, 'children'): + if isinstance(x, gr.Tabs) and x.elem_id is not None: + # Tabs element can't have a label, have to use elem_id instead + self.add_component(f"{path}/Tabs@{x.elem_id}", x) + for c in x.children: + self.add_block(c, path) + elif x.label is not None: + self.add_component(f"{path}/{x.label}", x) + + def read_from_file(self): + with open(self.filename, "r", encoding="utf8") as file: + return json.load(file) + + def write_to_file(self, current_ui_settings): + with open(self.filename, "w", encoding="utf8") as file: + json.dump(current_ui_settings, file, indent=4) + + def dump_defaults(self): + """saves default values to a file unless tjhe file is present and there was an error loading default values at start""" + + if self.error_loading and os.path.exists(self.filename): + return + + self.write_to_file(self.ui_settings) + + def iter_changes(self, current_ui_settings, values): + """ + given a dictionary with defaults from a file and current values from gradio elements, returns + an iterator over tuples of values that are not the same between the file and the current; + tuple contents are: path, old value, new value + """ + + for (path, component), new_value in zip(self.component_mapping.items(), values): + old_value = current_ui_settings.get(path) + + choices = getattr(component, 'choices', None) + if isinstance(new_value, int) and choices: + if new_value >= len(choices): + continue + + new_value = choices[new_value] + + if new_value == old_value: + continue + + if old_value is None and new_value == '' or new_value == []: + continue + + yield path, old_value, new_value + + def ui_view(self, *values): + text = [""] + + for path, old_value, new_value in self.iter_changes(self.read_from_file(), values): + if old_value is None: + old_value = "None" + + text.append(f"") + + if len(text) == 1: + text.append("") + + text.append("") + return "".join(text) + + def ui_apply(self, *values): + num_changed = 0 + + current_ui_settings = self.read_from_file() + + for path, _, new_value in self.iter_changes(current_ui_settings.copy(), values): + num_changed += 1 + current_ui_settings[path] = new_value + + if num_changed == 0: + return "No changes." + + self.write_to_file(current_ui_settings) + + return f"Wrote {num_changed} changes." + + def create_ui(self): + """creates ui elements for editing defaults UI, without adding any logic to them""" + + gr.HTML( + f"This page allows you to change default values in UI elements on other tabs.
" + f"Make your changes, press 'View changes' to review the changed default values,
" + f"then press 'Apply' to write them to {self.filename}.
" + f"New defaults will apply after you restart the UI.
" + ) + + with gr.Row(): + self.ui_defaults_view = gr.Button(value='View changes', elem_id="ui_defaults_view", variant="secondary") + self.ui_defaults_apply = gr.Button(value='Apply', elem_id="ui_defaults_apply", variant="primary") + + self.ui_defaults_review = gr.HTML("") + + def setup_ui(self): + """adds logic to elements created with create_ui; all add_block class must be made before this""" + + assert not self.finalized_ui + self.finalized_ui = True + + self.ui_defaults_view.click(fn=self.ui_view, inputs=list(self.component_mapping.values()), outputs=[self.ui_defaults_review]) + self.ui_defaults_apply.click(fn=self.ui_apply, inputs=list(self.component_mapping.values()), outputs=[self.ui_defaults_review]) -- cgit v1.2.3 From c8732dfa6f763332962d97ff040af156e24a9e62 Mon Sep 17 00:00:00 2001 From: Louis Del Valle <92354925+nero-dv@users.noreply.github.com> Date: Wed, 10 May 2023 22:05:18 -0500 Subject: Update sub_quadratic_attention.py 1. Determine the number of query chunks. 2. Calculate the final shape of the res tensor. 3. Initialize the tensor with the calculated shape and dtype, (same dtype as the input tensors, usually) Can initialize the tensor as a zero-filled tensor with the correct shape and dtype, then compute the attention scores for each query chunk and fill the corresponding slice of tensor. --- modules/sub_quadratic_attention.py | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) (limited to 'modules') diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py index 05595323..f80c1600 100644 --- a/modules/sub_quadratic_attention.py +++ b/modules/sub_quadratic_attention.py @@ -202,13 +202,22 @@ def efficient_dot_product_attention( value=value, ) - # TODO: maybe we should use torch.empty_like(query) to allocate storage in-advance, - # and pass slices to be mutated, instead of torch.cat()ing the returned slices - res = torch.cat([ - compute_query_chunk_attn( + # slices of res tensor are mutable, modifications made + # to the slices will affect the original tensor. + # if output of compute_query_chunk_attn function has same number of + # dimensions as input query tensor, we initialize tensor like this: + num_query_chunks = int(np.ceil(q_tokens / query_chunk_size)) + query_shape = get_query_chunk(0).shape + res_shape = (query_shape[0], query_shape[1] * num_query_chunks, *query_shape[2:]) + res_dtype = get_query_chunk(0).dtype + res = torch.zeros(res_shape, dtype=res_dtype) + + for i in range(num_query_chunks): + attn_scores = compute_query_chunk_attn( query=get_query_chunk(i * query_chunk_size), key=key, value=value, - ) for i in range(math.ceil(q_tokens / query_chunk_size)) - ], dim=1) + ) + res[:, i * query_chunk_size:(i + 1) * query_chunk_size, :] = attn_scores + return res -- cgit v1.2.3 From ae17e97898af8dd776b20e104ba9a81fe699e4df Mon Sep 17 00:00:00 2001 From: Sakura-Luna <53183413+Sakura-Luna@users.noreply.github.com> Date: Thu, 11 May 2023 12:26:04 +0800 Subject: UniPC progress bar adjustment --- modules/models/diffusion/uni_pc/uni_pc.py | 70 ++++++++++++++++--------------- 1 file changed, 37 insertions(+), 33 deletions(-) (limited to 'modules') diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index eb5f4e76..1d1b07bd 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -1,7 +1,7 @@ import torch import torch.nn.functional as F import math -from tqdm.auto import trange +import tqdm class NoiseScheduleVP: @@ -757,40 +757,44 @@ class UniPC: vec_t = timesteps[0].expand((x.shape[0])) model_prev_list = [self.model_fn(x, vec_t)] t_prev_list = [vec_t] - # Init the first `order` values by lower order multistep DPM-Solver. - for init_order in range(1, order): - vec_t = timesteps[init_order].expand(x.shape[0]) - x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, init_order, use_corrector=True) - if model_x is None: - model_x = self.model_fn(x, vec_t) - if self.after_update is not None: - self.after_update(x, model_x) - model_prev_list.append(model_x) - t_prev_list.append(vec_t) - for step in trange(order, steps + 1): - vec_t = timesteps[step].expand(x.shape[0]) - if lower_order_final: - step_order = min(order, steps + 1 - step) - else: - step_order = order - #print('this step order:', step_order) - if step == steps: - #print('do not run corrector at the last step') - use_corrector = False - else: - use_corrector = True - x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, step_order, use_corrector=use_corrector) - if self.after_update is not None: - self.after_update(x, model_x) - for i in range(order - 1): - t_prev_list[i] = t_prev_list[i + 1] - model_prev_list[i] = model_prev_list[i + 1] - t_prev_list[-1] = vec_t - # We do not need to evaluate the final model value. - if step < steps: + with tqdm.tqdm(total=steps) as pbar: + # Init the first `order` values by lower order multistep DPM-Solver. + for init_order in range(1, order): + vec_t = timesteps[init_order].expand(x.shape[0]) + x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, init_order, use_corrector=True) if model_x is None: model_x = self.model_fn(x, vec_t) - model_prev_list[-1] = model_x + if self.after_update is not None: + self.after_update(x, model_x) + model_prev_list.append(model_x) + t_prev_list.append(vec_t) + pbar.update() + + for step in range(order, steps + 1): + vec_t = timesteps[step].expand(x.shape[0]) + if lower_order_final: + step_order = min(order, steps + 1 - step) + else: + step_order = order + #print('this step order:', step_order) + if step == steps: + #print('do not run corrector at the last step') + use_corrector = False + else: + use_corrector = True + x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, step_order, use_corrector=use_corrector) + if self.after_update is not None: + self.after_update(x, model_x) + for i in range(order - 1): + t_prev_list[i] = t_prev_list[i + 1] + model_prev_list[i] = model_prev_list[i + 1] + t_prev_list[-1] = vec_t + # We do not need to evaluate the final model value. + if step < steps: + if model_x is None: + model_x = self.model_fn(x, vec_t) + model_prev_list[-1] = model_x + pbar.update() else: raise NotImplementedError() if denoise_to_zero: -- cgit v1.2.3 From e334758ec281eaf7723c806713721d12bb568e24 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 11 May 2023 07:45:05 +0300 Subject: repair #10266 --- modules/sub_quadratic_attention.py | 18 +++++------------- 1 file changed, 5 insertions(+), 13 deletions(-) (limited to 'modules') diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py index f80c1600..cc38debd 100644 --- a/modules/sub_quadratic_attention.py +++ b/modules/sub_quadratic_attention.py @@ -201,23 +201,15 @@ def efficient_dot_product_attention( key=key, value=value, ) - - # slices of res tensor are mutable, modifications made - # to the slices will affect the original tensor. - # if output of compute_query_chunk_attn function has same number of - # dimensions as input query tensor, we initialize tensor like this: - num_query_chunks = int(np.ceil(q_tokens / query_chunk_size)) - query_shape = get_query_chunk(0).shape - res_shape = (query_shape[0], query_shape[1] * num_query_chunks, *query_shape[2:]) - res_dtype = get_query_chunk(0).dtype - res = torch.zeros(res_shape, dtype=res_dtype) - - for i in range(num_query_chunks): + + res = torch.zeros_like(query) + for i in range(math.ceil(q_tokens / query_chunk_size)): attn_scores = compute_query_chunk_attn( query=get_query_chunk(i * query_chunk_size), key=key, value=value, ) - res[:, i * query_chunk_size:(i + 1) * query_chunk_size, :] = attn_scores + + res[:, i * query_chunk_size:i * query_chunk_size + attn_scores.shape[1], :] = attn_scores return res -- cgit v1.2.3 From b7e160a87d07b2fd1c12812c43786e141cc86bd5 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 11 May 2023 08:14:45 +0300 Subject: change live preview format to jpeg to prevent unreasonably slow previews for large images, and add an option to let user select the format --- modules/progress.py | 4 ++-- modules/shared.py | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/progress.py b/modules/progress.py index 948e6f00..289dd311 100644 --- a/modules/progress.py +++ b/modules/progress.py @@ -95,9 +95,9 @@ def progressapi(req: ProgressRequest): image = shared.state.current_image if image is not None: buffered = io.BytesIO() - image.save(buffered, format="png") + image.save(buffered, format=opts.live_previews_format) base64_image = base64.b64encode(buffered.getvalue()).decode('ascii') - live_preview = f"data:image/png;base64,{base64_image}" + live_preview = f"data:image/{opts.live_previews_format};base64,{base64_image}" id_live_preview = shared.state.id_live_preview else: live_preview = None diff --git a/modules/shared.py b/modules/shared.py index ac67adc0..fc39161e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -420,6 +420,7 @@ options_templates.update(options_section(('infotext', "Infotext"), { options_templates.update(options_section(('ui', "Live previews"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), + "live_previews_format": OptionInfo("jpeg", "Live preview file format", gr.Radio, {"choices": ["jpeg", "png", "webp"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), -- cgit v1.2.3 From 1dcd6723242c3d691610f9ed937951baea49c2d1 Mon Sep 17 00:00:00 2001 From: Sakura-Luna <53183413+Sakura-Luna@users.noreply.github.com> Date: Thu, 11 May 2023 14:29:52 +0800 Subject: Update sd_vae.py There is no need to use split. --- modules/sd_vae.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 17d1f702..95262ca3 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -88,10 +88,9 @@ def refresh_vae_list(): def find_vae_near_checkpoint(checkpoint_file): - checkpoint_path = os.path.basename(checkpoint_file).split('.', 1)[0] + checkpoint_path = os.path.basename(checkpoint_file).rsplit('.', 1)[0] for vae_file in vae_dict.values(): - vae_path = os.path.basename(vae_file).split('.', 1)[0] - if vae_path == checkpoint_path: + if os.path.basename(vae_file).startswith(checkpoint_path): return vae_file return None -- cgit v1.2.3 From 16e4d791224125cef2b91f7cf39893ceffd8bd74 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 10:05:39 +0300 Subject: paths_internal: deduplicate modules_path --- modules/paths_internal.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/paths_internal.py b/modules/paths_internal.py index 6765bafe..a3d3e1f8 100644 --- a/modules/paths_internal.py +++ b/modules/paths_internal.py @@ -3,7 +3,8 @@ import argparse import os -script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) +modules_path = os.path.dirname(os.path.realpath(__file__)) +script_path = os.path.dirname(modules_path) sd_configs_path = os.path.join(script_path, "configs") sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml") @@ -12,7 +13,7 @@ default_sd_model_file = sd_model_file # Parse the --data-dir flag first so we can use it as a base for our other argument default values parser_pre = argparse.ArgumentParser(add_help=False) -parser_pre.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) +parser_pre.add_argument("--data-dir", type=str, default=os.path.dirname(modules_path), help="base path where all user data is stored", ) cmd_opts_pre = parser_pre.parse_known_args()[0] data_path = cmd_opts_pre.data_dir -- cgit v1.2.3 From df7070eca22278b25c921ef72d3f97a221d66242 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 10:06:19 +0300 Subject: Deduplicate get_font code --- modules/images.py | 13 +++++++------ modules/textual_inversion/image_embedding.py | 9 ++------- 2 files changed, 9 insertions(+), 13 deletions(-) (limited to 'modules') diff --git a/modules/images.py b/modules/images.py index c4e98c75..d8527179 100644 --- a/modules/images.py +++ b/modules/images.py @@ -24,6 +24,13 @@ from modules.shared import opts LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) +def get_font(fontsize: int): + try: + return ImageFont.truetype(opts.font or Roboto, fontsize) + except Exception: + return ImageFont.truetype(Roboto, fontsize) + + def image_grid(imgs, batch_size=1, rows=None): if rows is None: if opts.n_rows > 0: @@ -142,12 +149,6 @@ def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0): lines.append(word) return lines - def get_font(fontsize): - try: - return ImageFont.truetype(opts.font or Roboto, fontsize) - except Exception: - return ImageFont.truetype(Roboto, fontsize) - def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize): for line in lines: fnt = initial_fnt diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py index d85a4888..5858a55f 100644 --- a/modules/textual_inversion/image_embedding.py +++ b/modules/textual_inversion/image_embedding.py @@ -3,9 +3,7 @@ import json import numpy as np import zlib from PIL import Image, ImageDraw, ImageFont -from fonts.ttf import Roboto import torch -from modules.shared import opts class EmbeddingEncoder(json.JSONEncoder): @@ -136,11 +134,8 @@ def caption_image_overlay(srcimage, title, footerLeft, footerMid, footerRight, t image = srcimage.copy() fontsize = 32 if textfont is None: - try: - textfont = ImageFont.truetype(opts.font or Roboto, fontsize) - textfont = opts.font or Roboto - except Exception: - textfont = Roboto + from modules.images import get_font + textfont = get_font(fontsize) factor = 1.5 gradient = Image.new('RGBA', (1, image.size[1]), color=(0, 0, 0, 0)) -- cgit v1.2.3 From 1332c46b71b169b889d7df420f3285d9022da5cc Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 10:07:01 +0300 Subject: Drop fonts + font-roboto deps since we only use the single regular cut of Roboto --- modules/Roboto-Regular.ttf | Bin 0 -> 305608 bytes modules/images.py | 6 +++--- modules/paths_internal.py | 2 ++ 3 files changed, 5 insertions(+), 3 deletions(-) create mode 100644 modules/Roboto-Regular.ttf (limited to 'modules') diff --git a/modules/Roboto-Regular.ttf b/modules/Roboto-Regular.ttf new file mode 100644 index 00000000..500b1045 Binary files /dev/null and b/modules/Roboto-Regular.ttf differ diff --git a/modules/images.py b/modules/images.py index d8527179..3b8b62d9 100644 --- a/modules/images.py +++ b/modules/images.py @@ -13,12 +13,12 @@ import numpy as np import piexif import piexif.helper from PIL import Image, ImageFont, ImageDraw, PngImagePlugin -from fonts.ttf import Roboto import string import json import hashlib from modules import sd_samplers, shared, script_callbacks, errors +from modules.paths_internal import roboto_ttf_file from modules.shared import opts LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) @@ -26,9 +26,9 @@ LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.L def get_font(fontsize: int): try: - return ImageFont.truetype(opts.font or Roboto, fontsize) + return ImageFont.truetype(opts.font or roboto_ttf_file, fontsize) except Exception: - return ImageFont.truetype(Roboto, fontsize) + return ImageFont.truetype(roboto_ttf_file, fontsize) def image_grid(imgs, batch_size=1, rows=None): diff --git a/modules/paths_internal.py b/modules/paths_internal.py index a3d3e1f8..a23f6d70 100644 --- a/modules/paths_internal.py +++ b/modules/paths_internal.py @@ -22,3 +22,5 @@ models_path = os.path.join(data_path, "models") extensions_dir = os.path.join(data_path, "extensions") extensions_builtin_dir = os.path.join(script_path, "extensions-builtin") config_states_dir = os.path.join(script_path, "config_states") + +roboto_ttf_file = os.path.join(modules_path, 'Roboto-Regular.ttf') -- cgit v1.2.3 From 0bfaf613a84613f41946da02571e0e467e88d273 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 11 May 2023 13:30:33 +0300 Subject: put the star where it belongs --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index fc39161e..f387b5ae 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", hypernetworks]}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { -- cgit v1.2.3 From 098d2fda5250f9f418fc641bd0f185cb461ee6d9 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 18:13:35 +0300 Subject: Reindent autocrop with 4 spaces --- modules/textual_inversion/autocrop.py | 202 +++++++++++++++++----------------- 1 file changed, 102 insertions(+), 100 deletions(-) (limited to 'modules') diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 7770d22f..8e667a4d 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -10,63 +10,64 @@ RED = "#F00" def crop_image(im, settings): - """ Intelligently crop an image to the subject matter """ - - scale_by = 1 - if is_landscape(im.width, im.height): - scale_by = settings.crop_height / im.height - elif is_portrait(im.width, im.height): - scale_by = settings.crop_width / im.width - elif is_square(im.width, im.height): - if is_square(settings.crop_width, settings.crop_height): - scale_by = settings.crop_width / im.width - elif is_landscape(settings.crop_width, settings.crop_height): - scale_by = settings.crop_width / im.width - elif is_portrait(settings.crop_width, settings.crop_height): - scale_by = settings.crop_height / im.height - - im = im.resize((int(im.width * scale_by), int(im.height * scale_by))) - im_debug = im.copy() - - focus = focal_point(im_debug, settings) - - # take the focal point and turn it into crop coordinates that try to center over the focal - # point but then get adjusted back into the frame - y_half = int(settings.crop_height / 2) - x_half = int(settings.crop_width / 2) - - x1 = focus.x - x_half - if x1 < 0: - x1 = 0 - elif x1 + settings.crop_width > im.width: - x1 = im.width - settings.crop_width - - y1 = focus.y - y_half - if y1 < 0: - y1 = 0 - elif y1 + settings.crop_height > im.height: - y1 = im.height - settings.crop_height - - x2 = x1 + settings.crop_width - y2 = y1 + settings.crop_height - - crop = [x1, y1, x2, y2] - - results = [] - - results.append(im.crop(tuple(crop))) - - if settings.annotate_image: - d = ImageDraw.Draw(im_debug) - rect = list(crop) - rect[2] -= 1 - rect[3] -= 1 - d.rectangle(rect, outline=GREEN) - results.append(im_debug) - if settings.destop_view_image: - im_debug.show() - - return results + """ Intelligently crop an image to the subject matter """ + + scale_by = 1 + if is_landscape(im.width, im.height): + scale_by = settings.crop_height / im.height + elif is_portrait(im.width, im.height): + scale_by = settings.crop_width / im.width + elif is_square(im.width, im.height): + if is_square(settings.crop_width, settings.crop_height): + scale_by = settings.crop_width / im.width + elif is_landscape(settings.crop_width, settings.crop_height): + scale_by = settings.crop_width / im.width + elif is_portrait(settings.crop_width, settings.crop_height): + scale_by = settings.crop_height / im.height + + + im = im.resize((int(im.width * scale_by), int(im.height * scale_by))) + im_debug = im.copy() + + focus = focal_point(im_debug, settings) + + # take the focal point and turn it into crop coordinates that try to center over the focal + # point but then get adjusted back into the frame + y_half = int(settings.crop_height / 2) + x_half = int(settings.crop_width / 2) + + x1 = focus.x - x_half + if x1 < 0: + x1 = 0 + elif x1 + settings.crop_width > im.width: + x1 = im.width - settings.crop_width + + y1 = focus.y - y_half + if y1 < 0: + y1 = 0 + elif y1 + settings.crop_height > im.height: + y1 = im.height - settings.crop_height + + x2 = x1 + settings.crop_width + y2 = y1 + settings.crop_height + + crop = [x1, y1, x2, y2] + + results = [] + + results.append(im.crop(tuple(crop))) + + if settings.annotate_image: + d = ImageDraw.Draw(im_debug) + rect = list(crop) + rect[2] -= 1 + rect[3] -= 1 + d.rectangle(rect, outline=GREEN) + results.append(im_debug) + if settings.destop_view_image: + im_debug.show() + + return results def focal_point(im, settings): corner_points = image_corner_points(im, settings) if settings.corner_points_weight > 0 else [] @@ -86,7 +87,7 @@ def focal_point(im, settings): corner_centroid = None if len(corner_points) > 0: corner_centroid = centroid(corner_points) - corner_centroid.weight = settings.corner_points_weight / weight_pref_total + corner_centroid.weight = settings.corner_points_weight / weight_pref_total pois.append(corner_centroid) entropy_centroid = None @@ -98,7 +99,7 @@ def focal_point(im, settings): face_centroid = None if len(face_points) > 0: face_centroid = centroid(face_points) - face_centroid.weight = settings.face_points_weight / weight_pref_total + face_centroid.weight = settings.face_points_weight / weight_pref_total pois.append(face_centroid) average_point = poi_average(pois, settings) @@ -132,7 +133,7 @@ def focal_point(im, settings): d.rectangle(f.bounding(4), outline=color) d.ellipse(average_point.bounding(max_size), outline=GREEN) - + return average_point @@ -260,10 +261,11 @@ def image_entropy(im): hist = hist[hist > 0] return -np.log2(hist / hist.sum()).sum() + def centroid(pois): - x = [poi.x for poi in pois] - y = [poi.y for poi in pois] - return PointOfInterest(sum(x)/len(pois), sum(y)/len(pois)) + x = [poi.x for poi in pois] + y = [poi.y for poi in pois] + return PointOfInterest(sum(x) / len(pois), sum(y) / len(pois)) def poi_average(pois, settings): @@ -281,59 +283,59 @@ def poi_average(pois, settings): def is_landscape(w, h): - return w > h + return w > h def is_portrait(w, h): - return h > w + return h > w def is_square(w, h): - return w == h + return w == h def download_and_cache_models(dirname): - download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true' - model_file_name = 'face_detection_yunet.onnx' + download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true' + model_file_name = 'face_detection_yunet.onnx' - if not os.path.exists(dirname): - os.makedirs(dirname) + if not os.path.exists(dirname): + os.makedirs(dirname) - cache_file = os.path.join(dirname, model_file_name) - if not os.path.exists(cache_file): - print(f"downloading face detection model from '{download_url}' to '{cache_file}'") - response = requests.get(download_url) - with open(cache_file, "wb") as f: - f.write(response.content) + cache_file = os.path.join(dirname, model_file_name) + if not os.path.exists(cache_file): + print(f"downloading face detection model from '{download_url}' to '{cache_file}'") + response = requests.get(download_url) + with open(cache_file, "wb") as f: + f.write(response.content) - if os.path.exists(cache_file): - return cache_file - return None + if os.path.exists(cache_file): + return cache_file + return None class PointOfInterest: - def __init__(self, x, y, weight=1.0, size=10): - self.x = x - self.y = y - self.weight = weight - self.size = size + def __init__(self, x, y, weight=1.0, size=10): + self.x = x + self.y = y + self.weight = weight + self.size = size - def bounding(self, size): - return [ - self.x - size//2, - self.y - size//2, - self.x + size//2, - self.y + size//2 - ] + def bounding(self, size): + return [ + self.x - size // 2, + self.y - size // 2, + self.x + size // 2, + self.y + size // 2 + ] class Settings: - def __init__(self, crop_width=512, crop_height=512, corner_points_weight=0.5, entropy_points_weight=0.5, face_points_weight=0.5, annotate_image=False, dnn_model_path=None): - self.crop_width = crop_width - self.crop_height = crop_height - self.corner_points_weight = corner_points_weight - self.entropy_points_weight = entropy_points_weight - self.face_points_weight = face_points_weight - self.annotate_image = annotate_image - self.destop_view_image = False - self.dnn_model_path = dnn_model_path + def __init__(self, crop_width=512, crop_height=512, corner_points_weight=0.5, entropy_points_weight=0.5, face_points_weight=0.5, annotate_image=False, dnn_model_path=None): + self.crop_width = crop_width + self.crop_height = crop_height + self.corner_points_weight = corner_points_weight + self.entropy_points_weight = entropy_points_weight + self.face_points_weight = face_points_weight + self.annotate_image = annotate_image + self.destop_view_image = False + self.dnn_model_path = dnn_model_path -- cgit v1.2.3 From cb3f8ff59fe8f142c3ca074b8cbaaf83357f9dc1 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Thu, 11 May 2023 15:55:43 +0000 Subject: Fix symlink scanning --- modules/shared.py | 2 +- modules/ui_extra_networks.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index f387b5ae..210424ac 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -741,7 +741,7 @@ def walk_files(path, allowed_extensions=None): if allowed_extensions is not None: allowed_extensions = set(allowed_extensions) - for root, _, files in os.walk(path): + for root, _, files in os.walk(path, followlinks=True): for filename in files: if allowed_extensions is not None: _, ext = os.path.splitext(filename) diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 2fd82e8e..e35d0bfe 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -90,7 +90,7 @@ class ExtraNetworksPage: subdirs = {} for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]: - for root, dirs, _ in os.walk(parentdir): + for root, dirs, _ in os.walk(parentdir, followlinks=True): for dirname in dirs: x = os.path.join(root, dirname) -- cgit v1.2.3 From 49a55b410b66b7dd9be9335d8a2e3a71e4f8b15c Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 18:28:15 +0300 Subject: Autofix Ruff W (not W605) (mostly whitespace) --- modules/api/api.py | 4 +-- modules/api/models.py | 2 +- modules/cmd_args.py | 2 +- modules/codeformer/codeformer_arch.py | 14 +++++----- modules/codeformer/vqgan_arch.py | 38 +++++++++++++------------- modules/esrgan_model_arch.py | 4 +-- modules/extras.py | 2 +- modules/hypernetworks/hypernetwork.py | 12 ++++---- modules/images.py | 2 +- modules/mac_specific.py | 4 +-- modules/masking.py | 2 +- modules/ngrok.py | 4 +-- modules/processing.py | 2 +- modules/script_callbacks.py | 14 +++++----- modules/sd_hijack.py | 12 ++++---- modules/sd_hijack_optimizations.py | 32 +++++++++++----------- modules/sd_models.py | 4 +-- modules/sd_samplers_kdiffusion.py | 18 ++++++------ modules/sub_quadratic_attention.py | 2 +- modules/textual_inversion/dataset.py | 4 +-- modules/textual_inversion/preprocess.py | 2 +- modules/textual_inversion/textual_inversion.py | 16 +++++------ modules/ui.py | 18 ++++++------ modules/ui_extensions.py | 6 ++-- modules/xlmr.py | 6 ++-- 25 files changed, 113 insertions(+), 113 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index 594fa655..165985c3 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -227,7 +227,7 @@ class Api: script_idx = script_name_to_index(script_name, script_runner.selectable_scripts) script = script_runner.selectable_scripts[script_idx] return script, script_idx - + def get_scripts_list(self): t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] @@ -237,7 +237,7 @@ class Api: def get_script(self, script_name, script_runner): if script_name is None or script_name == "": return None, None - + script_idx = script_name_to_index(script_name, script_runner.scripts) return script_runner.scripts[script_idx] diff --git a/modules/api/models.py b/modules/api/models.py index 4d291076..006ccdb7 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -289,4 +289,4 @@ class MemoryResponse(BaseModel): class ScriptsList(BaseModel): txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)") - img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)") \ No newline at end of file + img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)") diff --git a/modules/cmd_args.py b/modules/cmd_args.py index e01ca655..f4a4ab36 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -102,4 +102,4 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers") parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False) parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False) -parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy') \ No newline at end of file +parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy') diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 45c70f84..12db6814 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -119,7 +119,7 @@ class TransformerSALayer(nn.Module): tgt_mask: Optional[Tensor] = None, tgt_key_padding_mask: Optional[Tensor] = None, query_pos: Optional[Tensor] = None): - + # self attention tgt2 = self.norm1(tgt) q = k = self.with_pos_embed(tgt2, query_pos) @@ -159,7 +159,7 @@ class Fuse_sft_block(nn.Module): @ARCH_REGISTRY.register() class CodeFormer(VQAutoEncoder): - def __init__(self, dim_embd=512, n_head=8, n_layers=9, + def __init__(self, dim_embd=512, n_head=8, n_layers=9, codebook_size=1024, latent_size=256, connect_list=('32', '64', '128', '256'), fix_modules=('quantize', 'generator')): @@ -179,14 +179,14 @@ class CodeFormer(VQAutoEncoder): self.feat_emb = nn.Linear(256, self.dim_embd) # transformer - self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0) + self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0) for _ in range(self.n_layers)]) # logits_predict head self.idx_pred_layer = nn.Sequential( nn.LayerNorm(dim_embd), nn.Linear(dim_embd, codebook_size, bias=False)) - + self.channels = { '16': 512, '32': 256, @@ -221,7 +221,7 @@ class CodeFormer(VQAutoEncoder): enc_feat_dict = {} out_list = [self.fuse_encoder_block[f_size] for f_size in self.connect_list] for i, block in enumerate(self.encoder.blocks): - x = block(x) + x = block(x) if i in out_list: enc_feat_dict[str(x.shape[-1])] = x.clone() @@ -266,11 +266,11 @@ class CodeFormer(VQAutoEncoder): fuse_list = [self.fuse_generator_block[f_size] for f_size in self.connect_list] for i, block in enumerate(self.generator.blocks): - x = block(x) + x = block(x) if i in fuse_list: # fuse after i-th block f_size = str(x.shape[-1]) if w>0: x = self.fuse_convs_dict[f_size](enc_feat_dict[f_size].detach(), x, w) out = x # logits doesn't need softmax before cross_entropy loss - return out, logits, lq_feat \ No newline at end of file + return out, logits, lq_feat diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index b24a0394..09ee6660 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -13,7 +13,7 @@ from basicsr.utils.registry import ARCH_REGISTRY def normalize(in_channels): return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True) - + @torch.jit.script def swish(x): @@ -210,15 +210,15 @@ class AttnBlock(nn.Module): # compute attention b, c, h, w = q.shape q = q.reshape(b, c, h*w) - q = q.permute(0, 2, 1) + q = q.permute(0, 2, 1) k = k.reshape(b, c, h*w) - w_ = torch.bmm(q, k) + w_ = torch.bmm(q, k) w_ = w_ * (int(c)**(-0.5)) w_ = F.softmax(w_, dim=2) # attend to values v = v.reshape(b, c, h*w) - w_ = w_.permute(0, 2, 1) + w_ = w_.permute(0, 2, 1) h_ = torch.bmm(v, w_) h_ = h_.reshape(b, c, h, w) @@ -270,18 +270,18 @@ class Encoder(nn.Module): def forward(self, x): for block in self.blocks: x = block(x) - + return x class Generator(nn.Module): def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions): super().__init__() - self.nf = nf - self.ch_mult = ch_mult + self.nf = nf + self.ch_mult = ch_mult self.num_resolutions = len(self.ch_mult) self.num_res_blocks = res_blocks - self.resolution = img_size + self.resolution = img_size self.attn_resolutions = attn_resolutions self.in_channels = emb_dim self.out_channels = 3 @@ -315,24 +315,24 @@ class Generator(nn.Module): blocks.append(nn.Conv2d(block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1)) self.blocks = nn.ModuleList(blocks) - + def forward(self, x): for block in self.blocks: x = block(x) - + return x - + @ARCH_REGISTRY.register() class VQAutoEncoder(nn.Module): def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=None, codebook_size=1024, emb_dim=256, beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None): super().__init__() logger = get_root_logger() - self.in_channels = 3 - self.nf = nf - self.n_blocks = res_blocks + self.in_channels = 3 + self.nf = nf + self.n_blocks = res_blocks self.codebook_size = codebook_size self.embed_dim = emb_dim self.ch_mult = ch_mult @@ -363,11 +363,11 @@ class VQAutoEncoder(nn.Module): self.kl_weight ) self.generator = Generator( - self.nf, + self.nf, self.embed_dim, - self.ch_mult, - self.n_blocks, - self.resolution, + self.ch_mult, + self.n_blocks, + self.resolution, self.attn_resolutions ) @@ -432,4 +432,4 @@ class VQGANDiscriminator(nn.Module): raise ValueError('Wrong params!') def forward(self, x): - return self.main(x) \ No newline at end of file + return self.main(x) diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 4de9dd8d..2b9888ba 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -105,7 +105,7 @@ class ResidualDenseBlock_5C(nn.Module): Modified options that can be used: - "Partial Convolution based Padding" arXiv:1811.11718 - "Spectral normalization" arXiv:1802.05957 - - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C. + - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C. {Rakotonirina} and A. {Rasoanaivo} """ @@ -170,7 +170,7 @@ class GaussianNoise(nn.Module): scale = self.sigma * x.detach() if self.is_relative_detach else self.sigma * x sampled_noise = self.noise.repeat(*x.size()).normal_() * scale x = x + sampled_noise - return x + return x def conv1x1(in_planes, out_planes, stride=1): return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False) diff --git a/modules/extras.py b/modules/extras.py index eb4f0b42..bdf9b3b7 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -199,7 +199,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ result_is_inpainting_model = True else: theta_0[key] = theta_func2(a, b, multiplier) - + theta_0[key] = to_half(theta_0[key], save_as_half) shared.state.sampling_step += 1 diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 38ef074f..570b5603 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -540,7 +540,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi return hypernetwork, filename scheduler = LearnRateScheduler(learn_rate, steps, initial_step) - + clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else None if clip_grad: clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, initial_step, verbose=False) @@ -593,7 +593,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi print(e) scaler = torch.cuda.amp.GradScaler() - + batch_size = ds.batch_size gradient_step = ds.gradient_step # n steps = batch_size * gradient_step * n image processed @@ -636,7 +636,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi if clip_grad: clip_grad_sched.step(hypernetwork.step) - + with devices.autocast(): x = batch.latent_sample.to(devices.device, non_blocking=pin_memory) if use_weight: @@ -657,14 +657,14 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi _loss_step += loss.item() scaler.scale(loss).backward() - + # go back until we reach gradient accumulation steps if (j + 1) % gradient_step != 0: continue loss_logging.append(_loss_step) if clip_grad: clip_grad(weights, clip_grad_sched.learn_rate) - + scaler.step(optimizer) scaler.update() hypernetwork.step += 1 @@ -674,7 +674,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi _loss_step = 0 steps_done = hypernetwork.step + 1 - + epoch_num = hypernetwork.step // steps_per_epoch epoch_step = hypernetwork.step % steps_per_epoch diff --git a/modules/images.py b/modules/images.py index 3b8b62d9..b2de3662 100644 --- a/modules/images.py +++ b/modules/images.py @@ -367,7 +367,7 @@ class FilenameGenerator: self.seed = seed self.prompt = prompt self.image = image - + def hasprompt(self, *args): lower = self.prompt.lower() if self.p is None or self.prompt is None: diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 5c2f92a1..d74c6b95 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -42,7 +42,7 @@ if has_mps: # MPS workaround for https://github.com/pytorch/pytorch/issues/79383 CondFunc('torch.Tensor.to', lambda orig_func, self, *args, **kwargs: orig_func(self.contiguous(), *args, **kwargs), lambda _, self, *args, **kwargs: self.device.type != 'mps' and (args and isinstance(args[0], torch.device) and args[0].type == 'mps' or isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps')) - # MPS workaround for https://github.com/pytorch/pytorch/issues/80800 + # MPS workaround for https://github.com/pytorch/pytorch/issues/80800 CondFunc('torch.nn.functional.layer_norm', lambda orig_func, *args, **kwargs: orig_func(*([args[0].contiguous()] + list(args[1:])), **kwargs), lambda _, *args, **kwargs: args and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps') # MPS workaround for https://github.com/pytorch/pytorch/issues/90532 @@ -60,4 +60,4 @@ if has_mps: # MPS workaround for https://github.com/pytorch/pytorch/issues/92311 if platform.processor() == 'i386': for funcName in ['torch.argmax', 'torch.Tensor.argmax']: - CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps') \ No newline at end of file + CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps') diff --git a/modules/masking.py b/modules/masking.py index a5c4d2da..be9f84c7 100644 --- a/modules/masking.py +++ b/modules/masking.py @@ -4,7 +4,7 @@ from PIL import Image, ImageFilter, ImageOps def get_crop_region(mask, pad=0): """finds a rectangular region that contains all masked ares in an image. Returns (x1, y1, x2, y2) coordinates of the rectangle. For example, if a user has painted the top-right part of a 512x512 image", the result may be (256, 0, 512, 256)""" - + h, w = mask.shape crop_left = 0 diff --git a/modules/ngrok.py b/modules/ngrok.py index 7a7b4b26..67a74e85 100644 --- a/modules/ngrok.py +++ b/modules/ngrok.py @@ -13,7 +13,7 @@ def connect(token, port, region): config = conf.PyngrokConfig( auth_token=token, region=region ) - + # Guard for existing tunnels existing = ngrok.get_tunnels(pyngrok_config=config) if existing: @@ -24,7 +24,7 @@ def connect(token, port, region): print(f'ngrok has already been connected to localhost:{port}! URL: {public_url}\n' 'You can use this link after the launch is complete.') return - + try: if account is None: public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url 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): diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 17109732..7d9dd736 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -32,22 +32,22 @@ class CFGDenoiserParams: def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond): self.x = x """Latent image representation in the process of being denoised""" - + self.image_cond = image_cond """Conditioning image""" - + self.sigma = sigma """Current sigma noise step value""" - + self.sampling_step = sampling_step """Current Sampling step number""" - + self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" - + self.text_cond = text_cond """ Encoder hidden states of text conditioning from prompt""" - + self.text_uncond = text_uncond """ Encoder hidden states of text conditioning from negative prompt""" @@ -240,7 +240,7 @@ def add_callback(callbacks, fun): callbacks.append(ScriptCallback(filename, fun)) - + def remove_current_script_callbacks(): stack = [x for x in inspect.stack() if x.filename != __file__] filename = stack[0].filename if len(stack) > 0 else 'unknown file' diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index e374aeb8..7e50f1ab 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -34,7 +34,7 @@ def apply_optimizations(): ldm.modules.diffusionmodules.model.nonlinearity = silu ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th - + optimization_method = None can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp @@ -92,12 +92,12 @@ def fix_checkpoint(): def weighted_loss(sd_model, pred, target, mean=True): #Calculate the weight normally, but ignore the mean loss = sd_model._old_get_loss(pred, target, mean=False) - + #Check if we have weights available weight = getattr(sd_model, '_custom_loss_weight', None) if weight is not None: loss *= weight - + #Return the loss, as mean if specified return loss.mean() if mean else loss @@ -105,7 +105,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): try: #Temporarily append weights to a place accessible during loss calc sd_model._custom_loss_weight = w - + #Replace 'get_loss' with a weight-aware one. Otherwise we need to reimplement 'forward' completely #Keep 'get_loss', but don't overwrite the previous old_get_loss if it's already set if not hasattr(sd_model, '_old_get_loss'): @@ -120,7 +120,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): del sd_model._custom_loss_weight except AttributeError: pass - + #If we have an old loss function, reset the loss function to the original one if hasattr(sd_model, '_old_get_loss'): sd_model.get_loss = sd_model._old_get_loss @@ -184,7 +184,7 @@ class StableDiffusionModelHijack: def undo_hijack(self, m): if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation: - m.cond_stage_model = m.cond_stage_model.wrapped + m.cond_stage_model = m.cond_stage_model.wrapped elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords: m.cond_stage_model = m.cond_stage_model.wrapped diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index a174bbe1..f00fe55c 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -62,10 +62,10 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None): end = i + 2 s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end]) s1 *= self.scale - + s2 = s1.softmax(dim=-1) del s1 - + r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end]) del s2 del q, k, v @@ -95,43 +95,43 @@ def split_cross_attention_forward(self, x, context=None, mask=None): with devices.without_autocast(disable=not shared.opts.upcast_attn): k_in = k_in * self.scale - + del context, x - + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in)) del q_in, k_in, v_in - + r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype) - + mem_free_total = get_available_vram() - + gb = 1024 ** 3 tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() modifier = 3 if q.element_size() == 2 else 2.5 mem_required = tensor_size * modifier steps = 1 - + if mem_required > mem_free_total: steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2))) # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB " # f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}") - + if steps > 64: max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64 raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). ' f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free') - + slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] for i in range(0, q.shape[1], slice_size): end = i + slice_size s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k) - + s2 = s1.softmax(dim=-1, dtype=q.dtype) del s1 - + r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v) del s2 - + del q, k, v r1 = r1.to(dtype) @@ -228,7 +228,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None): with devices.without_autocast(disable=not shared.opts.upcast_attn): k = k * self.scale - + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v)) r = einsum_op(q, k, v) r = r.to(dtype) @@ -369,7 +369,7 @@ def scaled_dot_product_attention_forward(self, x, context=None, mask=None): q = q_in.view(batch_size, -1, h, head_dim).transpose(1, 2) k = k_in.view(batch_size, -1, h, head_dim).transpose(1, 2) v = v_in.view(batch_size, -1, h, head_dim).transpose(1, 2) - + del q_in, k_in, v_in dtype = q.dtype @@ -451,7 +451,7 @@ def cross_attention_attnblock_forward(self, x): h3 += x return h3 - + def xformers_attnblock_forward(self, x): try: h_ = x diff --git a/modules/sd_models.py b/modules/sd_models.py index d1e946a5..3316d021 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -165,7 +165,7 @@ def model_hash(filename): def select_checkpoint(): model_checkpoint = shared.opts.sd_model_checkpoint - + checkpoint_info = checkpoint_alisases.get(model_checkpoint, None) if checkpoint_info is not None: return checkpoint_info @@ -372,7 +372,7 @@ def enable_midas_autodownload(): if not os.path.exists(path): if not os.path.exists(midas_path): mkdir(midas_path) - + print(f"Downloading midas model weights for {model_type} to {path}") request.urlretrieve(midas_urls[model_type], path) print(f"{model_type} downloaded") diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 2f733cf5..e9e41818 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -93,10 +93,10 @@ class CFGDenoiser(torch.nn.Module): if shared.sd_model.model.conditioning_key == "crossattn-adm": image_uncond = torch.zeros_like(image_cond) - make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm} + make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm} else: image_uncond = image_cond - make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]} + make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]} if not is_edit_model: x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x]) @@ -316,7 +316,7 @@ class KDiffusionSampler: sigma_sched = sigmas[steps - t_enc - 1:] xi = x + noise * sigma_sched[0] - + extra_params_kwargs = self.initialize(p) parameters = inspect.signature(self.func).parameters @@ -339,9 +339,9 @@ class KDiffusionSampler: self.model_wrap_cfg.init_latent = x self.last_latent = x extra_args={ - 'cond': conditioning, - 'image_cond': image_conditioning, - 'uncond': unconditional_conditioning, + 'cond': conditioning, + 'image_cond': image_conditioning, + 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale, 's_min_uncond': self.s_min_uncond } @@ -374,9 +374,9 @@ class KDiffusionSampler: self.last_latent = x samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={ - 'cond': conditioning, - 'image_cond': image_conditioning, - 'uncond': unconditional_conditioning, + 'cond': conditioning, + 'image_cond': image_conditioning, + 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale, 's_min_uncond': self.s_min_uncond }, disable=False, callback=self.callback_state, **extra_params_kwargs)) diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py index cc38debd..497568eb 100644 --- a/modules/sub_quadratic_attention.py +++ b/modules/sub_quadratic_attention.py @@ -179,7 +179,7 @@ def efficient_dot_product_attention( chunk_idx, min(query_chunk_size, q_tokens) ) - + summarize_chunk: SummarizeChunk = partial(_summarize_chunk, scale=scale) summarize_chunk: SummarizeChunk = partial(checkpoint, summarize_chunk) if use_checkpoint else summarize_chunk compute_query_chunk_attn: ComputeQueryChunkAttn = partial( diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 41610e03..b9621fc9 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -118,7 +118,7 @@ class PersonalizedBase(Dataset): weight = torch.ones(latent_sample.shape) else: weight = None - + if latent_sampling_method == "random": entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist, weight=weight) else: @@ -243,4 +243,4 @@ class BatchLoaderRandom(BatchLoader): return self def collate_wrapper_random(batch): - return BatchLoaderRandom(batch) \ No newline at end of file + return BatchLoaderRandom(batch) diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index d0cad09e..a009d8e8 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -125,7 +125,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr default=None ) return wh and center_crop(image, *wh) - + def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None): width = process_width diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 9e1b2b9a..d489ed1e 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -323,16 +323,16 @@ def tensorboard_add(tensorboard_writer, loss, global_step, step, learn_rate, epo tensorboard_add_scaler(tensorboard_writer, f"Learn rate/train/epoch-{epoch_num}", learn_rate, step) def tensorboard_add_scaler(tensorboard_writer, tag, value, step): - tensorboard_writer.add_scalar(tag=tag, + tensorboard_writer.add_scalar(tag=tag, scalar_value=value, global_step=step) def tensorboard_add_image(tensorboard_writer, tag, pil_image, step): # Convert a pil image to a torch tensor img_tensor = torch.as_tensor(np.array(pil_image, copy=True)) - img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0], + img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0], len(pil_image.getbands())) img_tensor = img_tensor.permute((2, 0, 1)) - + tensorboard_writer.add_image(tag, img_tensor, global_step=step) def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_model_every, create_image_every, log_directory, name="embedding"): @@ -402,7 +402,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st if initial_step >= steps: shared.state.textinfo = "Model has already been trained beyond specified max steps" return embedding, filename - + scheduler = LearnRateScheduler(learn_rate, steps, initial_step) clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else \ torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else \ @@ -412,7 +412,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st # dataset loading may take a while, so input validations and early returns should be done before this shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." old_parallel_processing_allowed = shared.parallel_processing_allowed - + if shared.opts.training_enable_tensorboard: tensorboard_writer = tensorboard_setup(log_directory) @@ -439,7 +439,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st optimizer_saved_dict = torch.load(f"{filename}.optim", map_location='cpu') if embedding.checksum() == optimizer_saved_dict.get('hash', None): optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None) - + if optimizer_state_dict is not None: optimizer.load_state_dict(optimizer_state_dict) print("Loaded existing optimizer from checkpoint") @@ -485,7 +485,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st if clip_grad: clip_grad_sched.step(embedding.step) - + with devices.autocast(): x = batch.latent_sample.to(devices.device, non_blocking=pin_memory) if use_weight: @@ -513,7 +513,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st # go back until we reach gradient accumulation steps if (j + 1) % gradient_step != 0: continue - + if clip_grad: clip_grad(embedding.vec, clip_grad_sched.learn_rate) diff --git a/modules/ui.py b/modules/ui.py index 1efb656a..ff82fff6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1171,7 +1171,7 @@ def create_ui(): process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight") process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight") process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug") - + with gr.Column(visible=False) as process_multicrop_col: gr.Markdown('Each image is center-cropped with an automatically chosen width and height.') with gr.Row(): @@ -1183,7 +1183,7 @@ def create_ui(): with gr.Row(): process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective") process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold") - + with gr.Row(): with gr.Column(scale=3): gr.HTML(value="") @@ -1226,7 +1226,7 @@ def create_ui(): with FormRow(): embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate") hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate") - + with FormRow(): clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"]) clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False) @@ -1565,7 +1565,7 @@ def create_ui(): gr.HTML(shared.html("licenses.html"), elem_id="licenses") gr.Button(value="Show all pages", elem_id="settings_show_all_pages") - + def unload_sd_weights(): modules.sd_models.unload_model_weights() @@ -1841,15 +1841,15 @@ def versions_html(): return f""" version: {tag} - •  + • python: {python_version} - •  + • torch: {getattr(torch, '__long_version__',torch.__version__)} - •  + • xformers: {xformers_version} - •  + • gradio: {gr.__version__} - •  + • checkpoint: N/A """ diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index ed70abe5..af497733 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -467,7 +467,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=" - + """ for tag in [x for x in extension_tags if x not in tags]: @@ -535,9 +535,9 @@ def create_ui(): hide_tags = gr.CheckboxGroup(value=["ads", "localization", "installed"], label="Hide extensions with tags", choices=["script", "ads", "localization", "installed"]) sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order", ], type="index") - with gr.Row(): + with gr.Row(): search_extensions_text = gr.Text(label="Search").style(container=False) - + install_result = gr.HTML() available_extensions_table = gr.HTML() diff --git a/modules/xlmr.py b/modules/xlmr.py index e056c3f6..a407a3ca 100644 --- a/modules/xlmr.py +++ b/modules/xlmr.py @@ -28,7 +28,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): config_class = BertSeriesConfig def __init__(self, config=None, **kargs): - # modify initialization for autoloading + # modify initialization for autoloading if config is None: config = XLMRobertaConfig() config.attention_probs_dropout_prob= 0.1 @@ -74,7 +74,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): text["attention_mask"] = torch.tensor( text['attention_mask']).to(device) features = self(**text) - return features['projection_state'] + return features['projection_state'] def forward( self, @@ -134,4 +134,4 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): class RobertaSeriesModelWithTransformation(BertSeriesModelWithTransformation): base_model_prefix = 'roberta' - config_class= RobertaSeriesConfig \ No newline at end of file + config_class= RobertaSeriesConfig -- cgit v1.2.3 From da10de022f69e7847bcc64a7914d56246d852e20 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 20:52:30 +0300 Subject: Make live previews use JPEG only when the image is lorge enough --- modules/progress.py | 12 ++++++++++-- modules/shared.py | 2 +- 2 files changed, 11 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/progress.py b/modules/progress.py index 289dd311..c2e37834 100644 --- a/modules/progress.py +++ b/modules/progress.py @@ -95,9 +95,17 @@ def progressapi(req: ProgressRequest): image = shared.state.current_image if image is not None: buffered = io.BytesIO() - image.save(buffered, format=opts.live_previews_format) + format = opts.live_previews_format + save_kwargs = {} + if format == "auto": + if max(*image.size) > 256: + format = "jpeg" + else: + format = "png" + save_kwargs = {"optimize": True} + image.save(buffered, format=format, **save_kwargs) base64_image = base64.b64encode(buffered.getvalue()).decode('ascii') - live_preview = f"data:image/{opts.live_previews_format};base64,{base64_image}" + live_preview = f"data:image/{format};base64,{base64_image}" id_live_preview = shared.state.id_live_preview else: live_preview = None diff --git a/modules/shared.py b/modules/shared.py index f387b5ae..22b45618 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -420,7 +420,7 @@ options_templates.update(options_section(('infotext', "Infotext"), { options_templates.update(options_section(('ui', "Live previews"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), - "live_previews_format": OptionInfo("jpeg", "Live preview file format", gr.Radio, {"choices": ["jpeg", "png", "webp"]}), + "live_previews_format": OptionInfo("auto", "Live preview file format", gr.Radio, {"choices": ["auto", "jpeg", "png", "webp"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), -- cgit v1.2.3 From 681c16dd1e911bdf831b031b0f31aaba41c280f8 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Fri, 12 May 2023 22:33:21 +0900 Subject: fix --data-dir for COMMANDLINE_ARGS move reading of COMMANDLINE_ARGS into paths_internal.py so --data-dir can be properly read --- modules/paths_internal.py | 5 +++++ 1 file changed, 5 insertions(+) (limited to 'modules') diff --git a/modules/paths_internal.py b/modules/paths_internal.py index a23f6d70..005a9b0a 100644 --- a/modules/paths_internal.py +++ b/modules/paths_internal.py @@ -2,6 +2,11 @@ import argparse import os +import sys +import shlex + +commandline_args = os.environ.get('COMMANDLINE_ARGS', "") +sys.argv += shlex.split(commandline_args) modules_path = os.path.dirname(os.path.realpath(__file__)) script_path = os.path.dirname(modules_path) -- cgit v1.2.3 From 867be74244dc725fcf2685018b97501e83a16235 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Fri, 12 May 2023 18:08:34 +0000 Subject: Define default fonts for Gradio theme Allows web UI to (almost) be ran fully offline. The web UI will hang on load if offline when these fonts are not manually defined, as it will attempt (and fail) to pull from Google Fonts. --- modules/shared.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 1df1dd45..b09b384e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -666,13 +666,19 @@ def reload_gradio_theme(theme_name=None): theme_name = opts.gradio_theme if theme_name == "Default": - gradio_theme = gr.themes.Default() + gradio_theme = gr.themes.Default( + font=['Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) else: try: gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) except Exception as e: errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default() + gradio_theme = gr.themes.Default( + font=['Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) -- cgit v1.2.3 From 5afc44aab14819afea87b2f36c2f76dc43d3e83c Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sat, 13 May 2023 12:57:32 +0000 Subject: Requested changes --- modules/shared.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index b09b384e..96a20a6b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -665,20 +665,19 @@ def reload_gradio_theme(theme_name=None): if not theme_name: theme_name = opts.gradio_theme + default_theme_args = dict( + font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) + if theme_name == "Default": - gradio_theme = gr.themes.Default( - font=['Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) + gradio_theme = gr.themes.Default(**default_theme_args) else: try: gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) except Exception as e: errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default( - font=['Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) + gradio_theme = gr.themes.Default(**default_theme_args) -- 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/cmd_args.py | 1 - modules/processing.py | 10 +++++----- 2 files changed, 5 insertions(+), 6 deletions(-) (limited to 'modules') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 46043e33..f4a4ab36 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -102,5 +102,4 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers") parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False) parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False) -parser.add_argument("--token-merging", action='store_true', help="Provides speed and memory improvements by merging redundant tokens. This has a more pronounced effect on higher resolutions.", default=False) parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy') 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 cb5f61281a95be72fc812b7d350b6ec23e2f9bdd Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sat, 13 May 2023 11:04:26 -0400 Subject: Allow bf16 in safe unpickler --- modules/safe.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/safe.py b/modules/safe.py index 1e791c5b..e8f50774 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -40,7 +40,7 @@ class RestrictedUnpickler(pickle.Unpickler): return getattr(collections, name) if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter', '_rebuild_device_tensor_from_numpy']: return getattr(torch._utils, name) - if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32']: + if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32', 'BFloat16Storage']: return getattr(torch, name) if module == 'torch.nn.modules.container' and name in ['ParameterDict']: return getattr(torch.nn.modules.container, name) -- 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/generation_parameters_copypaste.py | 36 ------------------------- modules/processing.py | 35 +++++++++++-------------- modules/sd_models.py | 11 +++----- modules/shared.py | 42 +++--------------------------- 4 files changed, 23 insertions(+), 101 deletions(-) (limited to 'modules') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index fb56254f..a0a98bbc 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -282,33 +282,6 @@ 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 - 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' - if res.get("Token merging maximum down sampling", None) is None: - res["Token merging maximum down sampling"] = '1' - restore_old_hires_fix_params(res) # Missing RNG means the default was set, which is GPU RNG @@ -335,17 +308,8 @@ 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 down sampling', 'token_merging_maximum_down_sampling'), - ('Token merging stride x', 'token_merging_stride_x'), - ('Token merging stride y', 'token_merging_stride_y'), ('RNG', 'randn_source'), ('NGMS', 's_min_uncond') ] 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 diff --git a/modules/sd_models.py b/modules/sd_models.py index 4787193c..4c9a0a1f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -596,11 +596,8 @@ def apply_token_merging(sd_model, hr: bool): tomesd.apply_patch( sd_model, ratio=ratio, - max_downsample=shared.opts.token_merging_maximum_down_sampling, - sx=shared.opts.token_merging_stride_x, - sy=shared.opts.token_merging_stride_y, - use_rand=shared.opts.token_merging_random, - merge_attn=shared.opts.token_merging_merge_attention, - merge_crossattn=shared.opts.token_merging_merge_cross_attention, - merge_mlp=shared.opts.token_merging_merge_mlp + use_rand=False, # can cause issues with some samplers + merge_attn=True, + merge_crossattn=False, + merge_mlp=False ) diff --git a/modules/shared.py b/modules/shared.py index 4b346585..0d96c14c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -459,47 +459,13 @@ options_templates.update(options_section((None, "Hidden options"), { })) options_templates.update(options_section(('token_merging', 'Token Merging'), { - "token_merging": OptionInfo( - False, "Enable redundant token merging via tomesd. This can provide significant speed and memory improvements.", - gr.Checkbox - ), - "token_merging_ratio": OptionInfo( - 0.5, "Merging Ratio", - gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} - ), - "token_merging_hr_only": OptionInfo( - True, "Apply only to high-res fix pass. Disabling can yield a ~20-35% speedup on contemporary resolutions.", - gr.Checkbox - ), "token_merging_ratio_hr": OptionInfo( - 0.5, "Merging Ratio (high-res pass) - If 'Apply only to high-res' is enabled, this will always be the ratio used.", + 0, "Merging Ratio (high-res pass)", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} ), - # More advanced/niche settings: - "token_merging_random": OptionInfo( - False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visual artifacting.", - gr.Checkbox - ), - "token_merging_merge_attention": OptionInfo( - True, "Merge attention", - gr.Checkbox - ), - "token_merging_merge_cross_attention": OptionInfo( - False, "Merge cross attention", - gr.Checkbox - ), - "token_merging_merge_mlp": OptionInfo( - False, "Merge mlp", - gr.Checkbox - ), - "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": [1, 2, 4, 8]}), - "token_merging_stride_x": OptionInfo( - 2, "Stride - X", - gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} - ), - "token_merging_stride_y": OptionInfo( - 2, "Stride - Y", - gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} + "token_merging_ratio": OptionInfo( + 0, "Merging Ratio", + gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} ) })) -- cgit v1.2.3 From 917faa5325371e51d68f7d6f7b15ea4466bd5adf Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Sat, 13 May 2023 10:26:09 -0500 Subject: move to stable-diffusion tab --- modules/shared.py | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 0d96c14c..e49e9b74 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -350,6 +350,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}), + "token_merging_ratio_hr": OptionInfo(0, "Merging Ratio (high-res pass)", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}), + "token_merging_ratio": OptionInfo(0, "Merging Ratio", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}) })) options_templates.update(options_section(('compatibility', "Compatibility"), { @@ -458,16 +460,6 @@ options_templates.update(options_section((None, "Hidden options"), { "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) -options_templates.update(options_section(('token_merging', 'Token Merging'), { - "token_merging_ratio_hr": OptionInfo( - 0, "Merging Ratio (high-res pass)", - gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} - ), - "token_merging_ratio": OptionInfo( - 0, "Merging Ratio", - gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} - ) -})) options_templates.update() -- 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') 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 1f57b948b78df872c5a8a1c6e6c7e3c35e06f969 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Sat, 13 May 2023 19:14:10 +0300 Subject: Move localization to its own script block and load it first --- modules/localization.py | 4 ++-- modules/ui.py | 12 ++++++------ 2 files changed, 8 insertions(+), 8 deletions(-) (limited to 'modules') diff --git a/modules/localization.py b/modules/localization.py index f6a6f2fb..ee9c65e7 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -23,7 +23,7 @@ def list_localizations(dirname): localizations[fn] = file.path -def localization_js(current_localization_name): +def localization_js(current_localization_name: str) -> str: fn = localizations.get(current_localization_name, None) data = {} if fn is not None: @@ -34,4 +34,4 @@ def localization_js(current_localization_name): print(f"Error loading localization from {fn}:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - return f"var localization = {json.dumps(data)}\n" + return f"window.localization = {json.dumps(data)}" diff --git a/modules/ui.py b/modules/ui.py index ff82fff6..ff25c4ce 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1771,12 +1771,11 @@ def webpath(fn): def javascript_html(): - script_js = os.path.join(script_path, "script.js") - head = f'\n' + # Ensure localization is in `window` before scripts + head = f'\n' - inline = f"{localization.localization_js(shared.opts.localization)};" - if cmd_opts.theme is not None: - inline += f"set_theme('{cmd_opts.theme}');" + script_js = os.path.join(script_path, "script.js") + head += f'\n' for script in modules.scripts.list_scripts("javascript", ".js"): head += f'\n' @@ -1784,7 +1783,8 @@ def javascript_html(): for script in modules.scripts.list_scripts("javascript", ".mjs"): head += f'\n' - head += f'\n' + if cmd_opts.theme: + head += f'\n' return head -- cgit v1.2.3 From 7e3539df6f4e3979e080ed5d76faa3649c10f76f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 13 May 2023 20:21:11 +0300 Subject: fix upscalers disappearing after the user reloads UI --- modules/modelloader.py | 27 ++++++++++----------------- 1 file changed, 10 insertions(+), 17 deletions(-) (limited to 'modules') diff --git a/modules/modelloader.py b/modules/modelloader.py index cb85ac4f..a70aa0e3 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -117,20 +117,6 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None): pass -builtin_upscaler_classes = [] -forbidden_upscaler_classes = set() - - -def list_builtin_upscalers(): - builtin_upscaler_classes.clear() - builtin_upscaler_classes.extend(Upscaler.__subclasses__()) - -def forbid_loaded_nonbuiltin_upscalers(): - for cls in Upscaler.__subclasses__(): - if cls not in builtin_upscaler_classes: - forbidden_upscaler_classes.add(cls) - - def load_upscalers(): # We can only do this 'magic' method to dynamically load upscalers if they are referenced, # so we'll try to import any _model.py files before looking in __subclasses__ @@ -146,10 +132,17 @@ def load_upscalers(): datas = [] commandline_options = vars(shared.cmd_opts) - for cls in Upscaler.__subclasses__(): - if cls in forbidden_upscaler_classes: - continue + # some of upscaler classes will not go away after reloading their modules, and we'll end + # up with two copies of those classes. The newest copy will always be the last in the list, + # so we go from end to beginning and ignore duplicates + used_classes = {} + for cls in reversed(Upscaler.__subclasses__()): + classname = str(cls) + if classname not in used_classes: + used_classes[classname] = cls + + for cls in reversed(used_classes.values()): name = cls.__name__ cmd_name = f"{name.lower().replace('upscaler', '')}_models_path" scaler = cls(commandline_options.get(cmd_name, None)) -- cgit v1.2.3 From 063848798c4d4df6d3e108f4cc00c35ca38f5ebd Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 13 May 2023 19:45:18 +0300 Subject: Merge pull request #10339 from catboxanon/bf16 Allow bf16 in safe unpickler --- modules/safe.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/safe.py b/modules/safe.py index e6c2f2c0..e1a67f73 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -40,7 +40,7 @@ class RestrictedUnpickler(pickle.Unpickler): return getattr(collections, name) if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter', '_rebuild_device_tensor_from_numpy']: return getattr(torch._utils, name) - if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32']: + if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32', 'BFloat16Storage']: return getattr(torch, name) if module == 'torch.nn.modules.container' and name in ['ParameterDict']: return getattr(torch.nn.modules.container, name) -- cgit v1.2.3 From 12c78138dd56eef029ce74e371c8e646cb07f6fb Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 13 May 2023 19:43:15 +0300 Subject: Merge pull request #10324 from catboxanon/offline Allow web UI to be ran fully offline --- modules/shared.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 4631965b..b3508883 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -667,14 +667,19 @@ def reload_gradio_theme(theme_name=None): if not theme_name: theme_name = opts.gradio_theme + default_theme_args = dict( + font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) + if theme_name == "Default": - gradio_theme = gr.themes.Default() + gradio_theme = gr.themes.Default(**default_theme_args) else: try: gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) except Exception as e: errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default() + gradio_theme = gr.themes.Default(**default_theme_args) -- cgit v1.2.3 From 86ff43b930077aa41439c570fe41ad5de910455d Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 13 May 2023 19:44:55 +0300 Subject: Merge pull request #10335 from akx/l10n-dis-take-2 Localization fixes --- modules/localization.py | 4 ++-- modules/ui.py | 12 ++++++------ 2 files changed, 8 insertions(+), 8 deletions(-) (limited to 'modules') diff --git a/modules/localization.py b/modules/localization.py index f6a6f2fb..ee9c65e7 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -23,7 +23,7 @@ def list_localizations(dirname): localizations[fn] = file.path -def localization_js(current_localization_name): +def localization_js(current_localization_name: str) -> str: fn = localizations.get(current_localization_name, None) data = {} if fn is not None: @@ -34,4 +34,4 @@ def localization_js(current_localization_name): print(f"Error loading localization from {fn}:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - return f"var localization = {json.dumps(data)}\n" + return f"window.localization = {json.dumps(data)}" diff --git a/modules/ui.py b/modules/ui.py index d02f6e82..f07bcc41 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1863,12 +1863,11 @@ def webpath(fn): def javascript_html(): - script_js = os.path.join(script_path, "script.js") - head = f'\n' + # Ensure localization is in `window` before scripts + head = f'\n' - inline = f"{localization.localization_js(shared.opts.localization)};" - if cmd_opts.theme is not None: - inline += f"set_theme('{cmd_opts.theme}');" + script_js = os.path.join(script_path, "script.js") + head += f'\n' for script in modules.scripts.list_scripts("javascript", ".js"): head += f'\n' @@ -1876,7 +1875,8 @@ def javascript_html(): for script in modules.scripts.list_scripts("javascript", ".mjs"): head += f'\n' - head += f'\n' + if cmd_opts.theme: + head += f'\n' return head -- cgit v1.2.3 From 3078001439d25b66ef5627c9e3d431aa23bbed73 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sun, 14 May 2023 01:49:41 +0000 Subject: Add/modify CFG callbacks Required by self-attn guidance extension https://github.com/ashen-sensored/sd_webui_SAG --- modules/script_callbacks.py | 35 +++++++++++++++++++++++++++++++++++ modules/sd_samplers_kdiffusion.py | 8 +++++++- 2 files changed, 42 insertions(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 7d9dd736..e83c6ecf 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -53,6 +53,21 @@ class CFGDenoiserParams: class CFGDenoisedParams: + def __init__(self, x, sampling_step, total_sampling_steps, inner_model): + self.x = x + """Latent image representation in the process of being denoised""" + + self.sampling_step = sampling_step + """Current Sampling step number""" + + self.total_sampling_steps = total_sampling_steps + """Total number of sampling steps planned""" + + self.inner_model = inner_model + """Inner model reference that is being used for denoising""" + + +class AfterCFGCallbackParams: def __init__(self, x, sampling_step, total_sampling_steps): self.x = x """Latent image representation in the process of being denoised""" @@ -63,6 +78,9 @@ class CFGDenoisedParams: self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" + self.output_altered = False + """A flag for CFGDenoiser that indicates whether the output has been altered by the callback""" + class UiTrainTabParams: def __init__(self, txt2img_preview_params): @@ -87,6 +105,7 @@ callback_map = dict( callbacks_image_saved=[], callbacks_cfg_denoiser=[], callbacks_cfg_denoised=[], + callbacks_cfg_after_cfg=[], callbacks_before_component=[], callbacks_after_component=[], callbacks_image_grid=[], @@ -186,6 +205,14 @@ def cfg_denoised_callback(params: CFGDenoisedParams): report_exception(c, 'cfg_denoised_callback') +def cfg_after_cfg_callback(params: AfterCFGCallbackParams): + for c in callback_map['callbacks_cfg_after_cfg']: + try: + c.callback(params) + except Exception: + report_exception(c, 'cfg_after_cfg_callback') + + def before_component_callback(component, **kwargs): for c in callback_map['callbacks_before_component']: try: @@ -332,6 +359,14 @@ def on_cfg_denoised(callback): add_callback(callback_map['callbacks_cfg_denoised'], callback) +def on_cfg_after_cfg(callback): + """register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations has completed. + The callback is called with one argument: + - params: CFGDenoisedParams - parameters to be passed to the inner model and sampling state details. + """ + add_callback(callback_map['callbacks_cfg_after_cfg'], callback) + + def on_before_component(callback): """register a function to be called before a component is created. The callback is called with arguments: diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index e9e41818..55f0d3a3 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -8,6 +8,7 @@ from modules.shared import opts, state import modules.shared as shared from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback +from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback samplers_k_diffusion = [ ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}), @@ -160,7 +161,7 @@ class CFGDenoiser(torch.nn.Module): fake_uncond = torch.cat([x_out[i:i+1] for i in denoised_image_indexes]) x_out = torch.cat([x_out, fake_uncond]) # we skipped uncond denoising, so we put cond-denoised image to where the uncond-denoised image should be - denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps) + denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps, self.inner_model) cfg_denoised_callback(denoised_params) devices.test_for_nans(x_out, "unet") @@ -180,6 +181,11 @@ class CFGDenoiser(torch.nn.Module): if self.mask is not None: denoised = self.init_latent * self.mask + self.nmask * denoised + after_cfg_callback_params = AfterCFGCallbackParams(denoised, state.sampling_step, state.sampling_steps) + cfg_after_cfg_callback(after_cfg_callback_params) + if after_cfg_callback_params.output_altered: + denoised = after_cfg_callback_params.x + self.step += 1 return denoised -- cgit v1.2.3 From 8abfc95013d247c8a863d048574bc1f9d1eb0443 Mon Sep 17 00:00:00 2001 From: Sakura-Luna <53183413+Sakura-Luna@users.noreply.github.com> Date: Sun, 14 May 2023 12:56:34 +0800 Subject: Update script_callbacks.py --- modules/script_callbacks.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index e83c6ecf..57dfd457 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -64,7 +64,7 @@ class CFGDenoisedParams: """Total number of sampling steps planned""" self.inner_model = inner_model - """Inner model reference that is being used for denoising""" + """Inner model reference used for denoising""" class AfterCFGCallbackParams: @@ -79,7 +79,7 @@ class AfterCFGCallbackParams: """Total number of sampling steps planned""" self.output_altered = False - """A flag for CFGDenoiser that indicates whether the output has been altered by the callback""" + """A flag for CFGDenoiser indicating whether the output has been altered by the callback""" class UiTrainTabParams: @@ -360,9 +360,9 @@ def on_cfg_denoised(callback): def on_cfg_after_cfg(callback): - """register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations has completed. + """register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations are completed. The callback is called with one argument: - - params: CFGDenoisedParams - parameters to be passed to the inner model and sampling state details. + - params: AfterCFGCallbackParams - parameters to be passed to the script for post-processing after cfg calculation. """ add_callback(callback_map['callbacks_cfg_after_cfg'], callback) -- cgit v1.2.3 From 005849331e82cded96f6f3e5ff828037c672c38d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 08:15:22 +0300 Subject: remove output_altered flag from AfterCFGCallbackParams --- modules/script_callbacks.py | 3 --- modules/sd_samplers_kdiffusion.py | 3 +-- 2 files changed, 1 insertion(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 57dfd457..3c21a362 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -78,9 +78,6 @@ class AfterCFGCallbackParams: self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" - self.output_altered = False - """A flag for CFGDenoiser indicating whether the output has been altered by the callback""" - class UiTrainTabParams: def __init__(self, txt2img_preview_params): diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 55f0d3a3..61f23ad7 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -183,8 +183,7 @@ class CFGDenoiser(torch.nn.Module): after_cfg_callback_params = AfterCFGCallbackParams(denoised, state.sampling_step, state.sampling_steps) cfg_after_cfg_callback(after_cfg_callback_params) - if after_cfg_callback_params.output_altered: - denoised = after_cfg_callback_params.x + denoised = after_cfg_callback_params.x self.step += 1 return denoised -- cgit v1.2.3 From 2cfaffb239bb2b99aab06352f8c101e48e48dec9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 08:30:37 +0300 Subject: updates for #9256 --- modules/generation_parameters_copypaste.py | 2 +- modules/shared.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a0a98bbc..f1a2204c 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -311,7 +311,7 @@ infotext_to_setting_name_mapping = [ ('Token merging ratio', 'token_merging_ratio'), ('Token merging ratio hr', 'token_merging_ratio_hr'), ('RNG', 'randn_source'), - ('NGMS', 's_min_uncond') + ('NGMS', 's_min_uncond'), ] diff --git a/modules/shared.py b/modules/shared.py index a5e8d0bd..7ec9967e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -350,8 +350,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}), - "token_merging_ratio_hr": OptionInfo(0, "Merging Ratio (high-res pass)", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}), - "token_merging_ratio": OptionInfo(0, "Merging Ratio", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}) + "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), + "token_merging_ratio_hr": OptionInfo(0.0, "Togen merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), })) options_templates.update(options_section(('compatibility', "Compatibility"), { -- cgit v1.2.3 From ce515b81c57a2028ea515bd8f6f7984ba0f08963 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 10:02:51 +0300 Subject: set up a system to provide extra info for settings elements in python rather than js add a bit of spacing/styling to settings elements add link info for token merging --- modules/shared.py | 33 +++++++++++++++++++++++++++------ 1 file changed, 27 insertions(+), 6 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 7ec9967e..24fdcd59 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -199,8 +199,9 @@ interrogator = modules.interrogate.InterrogateModels("interrogate") face_restorers = [] + class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): self.default = default self.label = label self.component = component @@ -209,6 +210,24 @@ class OptionInfo: self.section = section self.refresh = refresh + self.comment_before = comment_before + """HTML text that will be added after label in UI""" + + self.comment_after = comment_after + """HTML text that will be added before label in UI""" + + def link(self, label, url): + self.comment_before += f"[{label}]" + return self + + def js(self, label, js_func): + self.comment_before += f"[{label}]" + return self + + def info(self, info): + self.comment_after += f"({info})" + return self + def options_section(section_identifier, options_dict): for v in options_dict.values(): @@ -240,7 +259,7 @@ options_templates = {} options_templates.update(options_section(('saving-images', "Saving images/grids"), { "samples_save": OptionInfo(True, "Always save all generated images"), "samples_format": OptionInfo('png', 'File format for images'), - "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs), + "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs), "grid_save": OptionInfo(True, "Always save all generated image grids"), @@ -290,7 +309,7 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo "save_to_dirs": OptionInfo(True, "Save images to a subdirectory"), "grid_save_to_dirs": OptionInfo(True, "Save grids to a subdirectory"), "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"), - "directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs), + "directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}), })) @@ -350,7 +369,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}), - "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), + "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), "token_merging_ratio_hr": OptionInfo(0.0, "Togen merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), })) @@ -404,7 +423,7 @@ options_templates.update(options_section(('ui', "User interface"), { "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}), + "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings"), "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}), "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"), "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"), @@ -572,7 +591,9 @@ class Options: func() def dumpjson(self): - d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()} + d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} + d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} + d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} return json.dumps(d) def add_option(self, key, info): -- cgit v1.2.3 From a423f23d289225a39d6f93a03bfda13eddbb42b7 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sun, 14 May 2023 16:22:40 +0900 Subject: allow jpeg for extra network preview --- modules/ui_extra_networks.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index e35d0bfe..0baccf56 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -30,7 +30,7 @@ def fetch_file(filename: str = ""): raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.") ext = os.path.splitext(filename)[1].lower() - if ext not in (".png", ".jpg", ".webp"): + if ext not in (".png", ".jpg", ".jpeg", ".webp"): raise ValueError(f"File cannot be fetched: {filename}. Only png and jpg and webp.") # would profit from returning 304 @@ -194,7 +194,7 @@ class ExtraNetworksPage: Find a preview PNG for a given path (without extension) and call link_preview on it. """ - preview_extensions = ["png", "jpg", "webp"] + preview_extensions = ["png", "jpg", "jpeg", "webp"] if shared.opts.samples_format not in preview_extensions: preview_extensions.append(shared.opts.samples_format) -- cgit v1.2.3 From a00e42556ffbc1b757fda5ba3f85a9e11c931441 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 11:04:21 +0300 Subject: add a bunch of descriptions and reword a lot of settings (sorry, localizers) --- modules/shared.py | 94 +++++++++++++++++++++++++++++-------------------------- 1 file changed, 49 insertions(+), 45 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 24fdcd59..a0577644 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -228,6 +228,12 @@ class OptionInfo: self.comment_after += f"({info})" return self + def needs_restart(self): + self.comment_after += " (requires restart)" + return self + + + def options_section(section_identifier, options_dict): for v in options_dict.values(): @@ -278,10 +284,10 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"), "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), "webp_lossless": OptionInfo(False, "Use lossless compression for webp images"), - "export_for_4chan": OptionInfo(True, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"), + "export_for_4chan": OptionInfo(True, "Save copy of large images as JPG").info("if the file size is above the limit, or either width or height are above the limit"), "img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number), "target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number), - "img_max_size_mp": OptionInfo(200, "Maximum image size, in megapixels", gr.Number), + "img_max_size_mp": OptionInfo(200, "Maximum image size", gr.Number).info("in megapixels"), "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"), "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"), @@ -314,23 +320,21 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo })) options_templates.update(options_section(('upscaling', "Upscaling"), { - "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}), - "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}), - "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), + "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), + "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), + "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), - "SCUNET_tile": OptionInfo(256, "Tile size for SCUNET upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}), - "SCUNET_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SCUNET upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}), })) options_templates.update(options_section(('face-restoration', "Face restoration"), { "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), - "code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), + "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), })) options_templates.update(options_section(('system', "System"), { "show_warnings": OptionInfo(False, "Show warnings in console."), - "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}), + "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"), "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"), "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."), "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), @@ -355,20 +359,20 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), - "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list), + "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), - "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."), + "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}), "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."), - "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"), + "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"), "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), - "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }), - "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), + "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), + "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP nrtwork; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), - "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}), + "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different vidocard vendors"), "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), "token_merging_ratio_hr": OptionInfo(0.0, "Togen merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), })) @@ -382,30 +386,32 @@ options_templates.update(options_section(('compatibility', "Compatibility"), { })) options_templates.update(options_section(('interrogate', "Interrogate Options"), { - "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), - "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."), - "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), - "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), - "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file (0 = No limit)"), + "interrogate_keep_models_in_memory": OptionInfo(False, "Keep models in VRAM"), + "interrogate_return_ranks": OptionInfo(False, "Include ranks of model tags matches in results.").info("booru only"), + "interrogate_clip_num_beams": OptionInfo(1, "BLIP: num_beams", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), + "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), + "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), + "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"), - "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"), - "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"), - "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"), + "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), + "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), + "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), + "deepbooru_escape": OptionInfo(True, "deepbooru: escape (\\) brackets").info("so they are used as literal brackets and not for emphasis"), + "deepbooru_filter_tags": OptionInfo("", "deepbooru: filter out those tags").info("separate by comma"), })) options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}), "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), - "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), - "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), + "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks").info("in pixels"), + "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"), + "extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"), "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { + "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), + "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), @@ -418,17 +424,15 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox_gamepad": OptionInfo(True, "Navigate image viewer with gamepad"), "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"), + "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group").needs_restart(), + "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_restart(), "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings"), - "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}), + "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_restart(), + "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"), - "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"), - "localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), - "gradio_theme": OptionInfo("Default", "Gradio theme (requires restart)", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}) + "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(), })) options_templates.update(options_section(('infotext', "Infotext"), { @@ -443,26 +447,26 @@ options_templates.update(options_section(('ui', "Live previews"), { "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), "live_previews_format": OptionInfo("auto", "Live preview file format", gr.Radio, {"choices": ["auto", "jpeg", "png", "webp"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), - "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), - "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), + "show_progress_every_n_steps": OptionInfo(10, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}).info("in sampling steps - show new live preview image every N sampling steps; -1 = only show after completion of batch"), + "show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}).info("Full = slow but pretty; Approx NN = fast but low quality; Approx cheap = super fast but terrible otherwise"), "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), - "live_preview_refresh_period": OptionInfo(1000, "Progressbar/preview update period, in milliseconds") + "live_preview_refresh_period": OptionInfo(1000, "Progressbar and preview update period").info("in milliseconds"), })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}), - "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_restart(), + "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), + "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_min_uncond': OptionInfo(0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"), + 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), + 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), - 'uni_pc_order': OptionInfo(3, "UniPC order (must be < sampling steps)", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}), + 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}).info("must be < sampling steps"), 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), })) -- cgit v1.2.3 From a58ae0b7174d9903fa426def2eda842dbbfcb53c Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 11:15:15 +0300 Subject: remove auto live previews format option, fix slow PNG generation --- modules/progress.py | 19 +++++++++---------- modules/shared.py | 2 +- 2 files changed, 10 insertions(+), 11 deletions(-) (limited to 'modules') diff --git a/modules/progress.py b/modules/progress.py index c2e37834..269863c9 100644 --- a/modules/progress.py +++ b/modules/progress.py @@ -95,17 +95,16 @@ def progressapi(req: ProgressRequest): image = shared.state.current_image if image is not None: buffered = io.BytesIO() - format = opts.live_previews_format - save_kwargs = {} - if format == "auto": - if max(*image.size) > 256: - format = "jpeg" - else: - format = "png" - save_kwargs = {"optimize": True} - image.save(buffered, format=format, **save_kwargs) + + if opts.live_previews_image_format == "png": + # using optimize for large images takes an enormous amount of time + save_kwargs = {"optimize": max(*image.size) > 256} + else: + save_kwargs = {} + + image.save(buffered, format=opts.live_previews_image_format, **save_kwargs) base64_image = base64.b64encode(buffered.getvalue()).decode('ascii') - live_preview = f"data:image/{format};base64,{base64_image}" + live_preview = f"data:image/{opts.live_previews_image_format};base64,{base64_image}" id_live_preview = shared.state.id_live_preview else: live_preview = None diff --git a/modules/shared.py b/modules/shared.py index a0577644..07f18b1b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -445,7 +445,7 @@ options_templates.update(options_section(('infotext', "Infotext"), { options_templates.update(options_section(('ui', "Live previews"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), - "live_previews_format": OptionInfo("auto", "Live preview file format", gr.Radio, {"choices": ["auto", "jpeg", "png", "webp"]}), + "live_previews_image_format": OptionInfo("png", "Live preview file format", gr.Radio, {"choices": ["jpeg", "png", "webp"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "show_progress_every_n_steps": OptionInfo(10, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}).info("in sampling steps - show new live preview image every N sampling steps; -1 = only show after completion of batch"), "show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}).info("Full = slow but pretty; Approx NN = fast but low quality; Approx cheap = super fast but terrible otherwise"), -- cgit v1.2.3 From 1a43524018ea3e64b93be2abc2a49b6159515442 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 13:27:50 +0300 Subject: fix model loading twice in some situations --- modules/sd_hijack.py | 3 +++ modules/sd_models.py | 3 +++ 2 files changed, 6 insertions(+) (limited to 'modules') diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 7e50f1ab..14e7f799 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -216,6 +216,9 @@ class StableDiffusionModelHijack: self.comments = [] def get_prompt_lengths(self, text): + if self.clip is None: + return "-", "-" + _, token_count = self.clip.process_texts([text]) return token_count, self.clip.get_target_prompt_token_count(token_count) diff --git a/modules/sd_models.py b/modules/sd_models.py index 4c9a0a1f..dddbc6e1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -414,6 +414,9 @@ class SdModelData: def get_sd_model(self): if self.sd_model is None: with self.lock: + if self.sd_model is not None: + return self.sd_model + try: load_model() except Exception as e: -- cgit v1.2.3 From 0d3a80e2692fb72da9798367b882f45312202f2e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 15 May 2023 20:33:44 +0300 Subject: Show "Loading..." for extra networks when displaying for the first time --- modules/ui_extra_networks.py | 19 +++++++++++++++---- 1 file changed, 15 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 0baccf56..752cf2b8 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -268,7 +268,7 @@ def create_ui(container, button, tabname): with gr.Tab(page.title, id=page_id): elem_id = f"{tabname}_{page_id}_cards_html" - page_elem = gr.HTML('', elem_id=elem_id) + page_elem = gr.HTML('Loading...', elem_id=elem_id) ui.pages.append(page_elem) page_elem.change(fn=lambda: None, _js='function(){applyExtraNetworkFilter(' + json.dumps(tabname) + '); return []}', inputs=[], outputs=[]) @@ -282,13 +282,24 @@ def create_ui(container, button, tabname): def toggle_visibility(is_visible): is_visible = not is_visible - if is_visible and not ui.pages_contents: + return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary")) + + def fill_tabs(is_empty): + """Creates HTML for extra networks' tabs when the extra networks button is clicked for the first time.""" + + if not ui.pages_contents: refresh() - return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary")), *ui.pages_contents + if is_empty: + return True, *ui.pages_contents + + return True, *[gr.update() for _ in ui.pages_contents] state_visible = gr.State(value=False) - button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button, *ui.pages]) + button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button], show_progress=False) + + state_empty = gr.State(value=True) + button.click(fn=fill_tabs, inputs=[state_empty], outputs=[state_empty, *ui.pages], show_progress=False) def refresh(): for pg in ui.stored_extra_pages: -- cgit v1.2.3 From 0d2a4b608c075daa3a4d1a1c9df01a763ae4793a Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 15 May 2023 20:57:11 +0300 Subject: load extensions' git metadata in parallel to loading the main program to save a ton of time during startup --- modules/config_states.py | 2 ++ modules/extensions.py | 12 +++++++++++- modules/ui_extensions.py | 15 +++++++++++++-- 3 files changed, 26 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/config_states.py b/modules/config_states.py index 75da862a..db65bcdb 100644 --- a/modules/config_states.py +++ b/modules/config_states.py @@ -83,6 +83,8 @@ def get_extension_config(): ext_config = {} for ext in extensions.extensions: + ext.read_info_from_repo() + entry = { "name": ext.name, "path": ext.path, diff --git a/modules/extensions.py b/modules/extensions.py index bc2c0450..1053253e 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -1,5 +1,6 @@ import os import sys +import threading import traceback import time @@ -24,6 +25,8 @@ def active(): class Extension: + lock = threading.Lock() + def __init__(self, name, path, enabled=True, is_builtin=False): self.name = name self.path = path @@ -42,8 +45,13 @@ class Extension: if self.is_builtin or self.have_info_from_repo: return - self.have_info_from_repo = True + with self.lock: + if self.have_info_from_repo: + return + self.do_read_info_from_repo() + + def do_read_info_from_repo(self): repo = None try: if os.path.exists(os.path.join(self.path, ".git")): @@ -70,6 +78,8 @@ class Extension: print(f"Failed reading extension data from Git repository ({self.name}): {ex}", file=sys.stderr) self.remote = None + self.have_info_from_repo = True + def list_files(self, subdir, extension): from modules import scripts diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index af497733..aaa7e571 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -1,6 +1,7 @@ import json import os.path import sys +import threading import time from datetime import datetime import traceback @@ -484,11 +485,18 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=" return code, list(tags) +def preload_extensions_git_metadata(): + for extension in extensions.extensions: + extension.read_info_from_repo() + + def create_ui(): import modules.ui config_states.list_config_states() + threading.Thread(target=preload_extensions_git_metadata).start() + with gr.Blocks(analytics_enabled=False) as ui: with gr.Tabs(elem_id="tabs_extensions"): with gr.TabItem("Installed", id="installed"): @@ -508,7 +516,8 @@ def create_ui(): """ info = gr.HTML(html) - extensions_table = gr.HTML(lambda: extension_table()) + extensions_table = gr.HTML('Loading...') + ui.load(fn=extension_table, inputs=[], outputs=[extensions_table]) apply.click( fn=apply_and_restart, @@ -595,7 +604,8 @@ def create_ui(): config_save_button = gr.Button(value="Save Current Config") config_states_info = gr.HTML("") - config_states_table = gr.HTML(lambda: update_config_states_table("Current")) + config_states_table = gr.HTML("Loading...") + ui.load(fn=update_config_states_table, inputs=[config_states_list], outputs=[config_states_table]) config_save_button.click(fn=save_config_state, inputs=[config_save_name], outputs=[config_states_list, config_states_info]) @@ -608,4 +618,5 @@ def create_ui(): outputs=[config_states_table], ) + return ui -- cgit v1.2.3 From a47abe1b7b667374e9df1932172230132d3fe8db Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 15 May 2023 21:22:35 +0300 Subject: update extensions table: show branch, show date in separate column, and show version from tags if available --- modules/extensions.py | 6 ++---- modules/ui_extensions.py | 7 ++++++- 2 files changed, 8 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/extensions.py b/modules/extensions.py index 1053253e..f16f059e 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -66,13 +66,11 @@ class Extension: try: self.status = 'unknown' self.remote = next(repo.remote().urls, None) - head = repo.head.commit self.commit_date = repo.head.commit.committed_date - ts = time.asctime(time.gmtime(self.commit_date)) if repo.active_branch: self.branch = repo.active_branch.name - self.commit_hash = head.hexsha - self.version = f'{self.commit_hash[:8]} ({ts})' + self.commit_hash = repo.head.commit.hexsha + self.version = repo.git.describe("--always", "--tags") # compared to `self.commit_hash[:8]` this takes about 30% more time total but since we run it in parallel we don't care except Exception as ex: print(f"Failed reading extension data from Git repository ({self.name}): {ex}", file=sys.stderr) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index aaa7e571..6ad9a97c 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -141,7 +141,9 @@ def extension_table(): - + + + @@ -149,6 +151,7 @@ def extension_table(): """ for ext in extensions.extensions: + ext: extensions.Extension ext.read_info_from_repo() remote = f"""{html.escape("built-in" if ext.is_builtin else ext.remote or '')}""" @@ -170,7 +173,9 @@ def extension_table(): + + {ext_status} """ -- cgit v1.2.3 From 3d76eabbca3adb711787d1802d6b61c0971b4bc0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 16 May 2023 07:59:43 +0300 Subject: add visual progress for extension installation from URL --- modules/extensions.py | 1 - modules/ui_extensions.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/extensions.py b/modules/extensions.py index f16f059e..359a7aa5 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -3,7 +3,6 @@ import sys import threading import traceback -import time import git from modules import shared diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 6ad9a97c..d7a0f685 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -593,9 +593,9 @@ def create_ui(): install_result = gr.HTML(elem_id="extension_install_result") install_button.click( - fn=modules.ui.wrap_gradio_call(install_extension_from_url, extra_outputs=[gr.update()]), + fn=modules.ui.wrap_gradio_call(lambda *args: [gr.update(), *install_extension_from_url(*args)], extra_outputs=[gr.update(), gr.update()]), inputs=[install_dirname, install_url, install_branch], - outputs=[extensions_table, install_result], + outputs=[install_url, extensions_table, install_result], ) with gr.TabItem("Backup/Restore"): -- 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 +++++++---- modules/sd_samplers.py | 8 +++++++- modules/sd_samplers_common.py | 21 ++++++++++++++++++++- modules/sd_samplers_compvis.py | 8 ++++++-- modules/sd_samplers_kdiffusion.py | 16 ++++++++-------- 5 files changed, 48 insertions(+), 16 deletions(-) (limited to 'modules') 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 "" diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 4f1bf21d..f22aad8f 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -14,12 +14,18 @@ samplers_for_img2img = [] samplers_map = {} -def create_sampler(name, model): +def find_sampler_config(name): if name is not None: config = all_samplers_map.get(name, None) else: config = all_samplers[0] + return config + + +def create_sampler(name, model): + config = find_sampler_config(name) + assert config is not None, f'bad sampler name: {name}' sampler = config.constructor(model) diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index bc074238..92880caf 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -2,7 +2,7 @@ from collections import namedtuple import numpy as np import torch from PIL import Image -from modules import devices, processing, images, sd_vae_approx +from modules import devices, processing, images, sd_vae_approx, sd_samplers from modules.shared import opts, state import modules.shared as shared @@ -58,6 +58,25 @@ def store_latent(decoded): shared.state.assign_current_image(sample_to_image(decoded)) +def is_sampler_using_eta_noise_seed_delta(p): + """returns whether sampler from config will use eta noise seed delta for image creation""" + + sampler_config = sd_samplers.find_sampler_config(p.sampler_name) + + eta = p.eta + + if eta is None and p.sampler is not None: + eta = p.sampler.eta + + if eta is None and sampler_config is not None: + eta = 0 if sampler_config.options.get("default_eta_is_0", False) else 1.0 + + if eta == 0: + return False + + return sampler_config.options.get("uses_ensd", False) + + class InterruptedException(BaseException): pass diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index b1ee3be7..bdae8b40 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -11,7 +11,7 @@ import modules.models.diffusion.uni_pc samplers_data_compvis = [ - sd_samplers_common.SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {}), + sd_samplers_common.SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {"default_eta_is_0": True, "uses_ensd": True}), sd_samplers_common.SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), [], {}), sd_samplers_common.SamplerData('UniPC', lambda model: VanillaStableDiffusionSampler(modules.models.diffusion.uni_pc.UniPCSampler, model), [], {}), ] @@ -134,7 +134,11 @@ class VanillaStableDiffusionSampler: self.update_step(x) def initialize(self, p): - self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim + if self.is_ddim: + self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim + else: + self.eta = 0.0 + if self.eta != 0.0: p.extra_generation_params["Eta DDIM"] = self.eta diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 61f23ad7..5455561a 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -11,21 +11,21 @@ from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback samplers_k_diffusion = [ - ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}), + ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {"uses_ensd": True}), ('Euler', 'sample_euler', ['k_euler'], {}), ('LMS', 'sample_lms', ['k_lms'], {}), ('Heun', 'sample_heun', ['k_heun'], {}), ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {'discard_next_to_last_sigma': True}), - ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {'discard_next_to_last_sigma': True}), - ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}), + ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {'discard_next_to_last_sigma': True, "uses_ensd": True}), + ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {"uses_ensd": True}), ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}), ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {}), - ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {}), - ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {}), + ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {"uses_ensd": True}), + ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {"uses_ensd": True}), ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}), - ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True}), - ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True}), - ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}), + ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}), + ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}), + ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras', "uses_ensd": True}), ('DPM++ 2M Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}), ('DPM++ SDE Karras', 'sample_dpmpp_sde', ['k_dpmpp_sde_ka'], {'scheduler': 'karras'}), ] -- 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 ++------ modules/sd_samplers_kdiffusion.py | 14 +++++++------- 2 files changed, 9 insertions(+), 13 deletions(-) (limited to 'modules') 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) diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 5455561a..552c6c64 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -14,20 +14,20 @@ samplers_k_diffusion = [ ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {"uses_ensd": True}), ('Euler', 'sample_euler', ['k_euler'], {}), ('LMS', 'sample_lms', ['k_lms'], {}), - ('Heun', 'sample_heun', ['k_heun'], {}), + ('Heun', 'sample_heun', ['k_heun'], {"second_order": True}), ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {'discard_next_to_last_sigma': True}), ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {'discard_next_to_last_sigma': True, "uses_ensd": True}), - ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {"uses_ensd": True}), + ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {"uses_ensd": True, "second_order": True}), ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}), - ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {}), + ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {"second_order": True}), ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {"uses_ensd": True}), ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {"uses_ensd": True}), ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}), - ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}), - ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}), - ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras', "uses_ensd": True}), + ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True, "second_order": True}), + ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True, "second_order": True}), + ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras', "uses_ensd": True, "second_order": True}), ('DPM++ 2M Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}), - ('DPM++ SDE Karras', 'sample_dpmpp_sde', ['k_dpmpp_sde_ka'], {'scheduler': 'karras'}), + ('DPM++ SDE Karras', 'sample_dpmpp_sde', ['k_dpmpp_sde_ka'], {'scheduler': 'karras', "second_order": True}), ] samplers_data_k_diffusion = [ -- cgit v1.2.3 From 6302978ff8e51ad0917c62806ca127b514088a70 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 16 May 2023 15:14:44 +0300 Subject: restore nqsp in footer that was lost during linting --- modules/ui.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/ui.py b/modules/ui.py index ff25c4ce..8e51e782 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1841,15 +1841,15 @@ def versions_html(): return f""" version: {tag} - • + •  python: {python_version} - • + •  torch: {getattr(torch, '__long_version__',torch.__version__)} - • + •  xformers: {xformers_version} - • + •  gradio: {gr.__version__} - • + •  checkpoint: N/A """ -- cgit v1.2.3 From ce38ee8f26d0b84888c72b58cdd9682ac3fd6151 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 16 May 2023 15:41:49 +0300 Subject: add info link for Negative Guidance minimum sigma --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 07f18b1b..3abf71c0 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -458,8 +458,8 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), + 's_min_uncond': OptionInfo(0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 's_min_uncond': OptionInfo(0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), -- cgit v1.2.3 From 54f657ffbc3c2e297d1d81c0e2026a68ccfbd602 Mon Sep 17 00:00:00 2001 From: dennissheng Date: Wed, 17 May 2023 10:47:02 +0800 Subject: not clear checkpoints cache when config changes --- modules/sd_models.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index 36f643e1..e37fcb8f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -538,7 +538,6 @@ def reload_model_weights(sd_model=None, info=None): if sd_model is None or checkpoint_config != sd_model.used_config: del sd_model - checkpoints_loaded.clear() load_model(checkpoint_info, already_loaded_state_dict=state_dict) return model_data.sd_model -- cgit v1.2.3
PathOld valueNew value
{path}{old_value}{new_value}
No changes
{html.escape(description)}

Added: {html.escape(added)}

 {install_code}
Extension URLVersionBranchVersionDate Update
{html.escape(ext.name)} {remote}{ext.branch} {version_link}{time.asctime(time.gmtime(ext.commit_date))}