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 ++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') 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') ] -- 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/generation_parameters_copypaste.py') 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 5fe0dd79beaa5ef737ff85254ee9870f60ae9464 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Apr 2023 11:29:37 +0300 Subject: rename CPU RNG to RNG source in settings, add infotext and parameters copypaste support to RNG source --- modules/devices.py | 4 ++-- modules/generation_parameters_copypaste.py | 5 +++++ modules/processing.py | 3 ++- modules/sd_samplers_common.py | 3 ++- modules/sd_samplers_kdiffusion.py | 2 +- modules/shared.py | 2 +- 6 files changed, 13 insertions(+), 6 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/devices.py b/modules/devices.py index 3bc86a6a..c705a3cb 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -95,7 +95,7 @@ def randn(seed, shape): from modules.shared import opts torch.manual_seed(seed) - if opts.use_cpu_randn or device.type == 'mps': + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) return torch.randn(shape, device=device) @@ -103,7 +103,7 @@ def randn(seed, shape): def randn_without_seed(shape): from modules.shared import opts - if opts.use_cpu_randn or device.type == 'mps': + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) return torch.randn(shape, device=device) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6df76858..e7269363 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -284,6 +284,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model restore_old_hires_fix_params(res) + # Missing RNG means the default was set, which is GPU RNG + if "RNG" not in res: + res["RNG"] = "GPU" + return res @@ -304,6 +308,7 @@ 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'), + ('RNG', 'randn_source'), ] diff --git a/modules/processing.py b/modules/processing.py index 5556afc5..7bac154d 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -477,7 +477,8 @@ 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, - "Init image hash": getattr(p, 'init_img_hash', None) + "Init image hash": getattr(p, 'init_img_hash', None), + "RNG": (opts.randn_source if opts.randn_source != "GPU" else None) } generation_params.update(p.extra_generation_params) diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index e6a372d5..bc074238 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -61,7 +61,8 @@ def store_latent(decoded): class InterruptedException(BaseException): pass -if opts.use_cpu_randn: + +if opts.randn_source == "CPU": import torchsde._brownian.brownian_interval def torchsde_randn(size, dtype, device, seed): diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 13f4567a..a547d1b5 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -190,7 +190,7 @@ class TorchHijack: if noise.shape == x.shape: return noise - if opts.use_cpu_randn or x.device.type == 'mps': + if opts.randn_source == "CPU" or x.device.type == 'mps': return torch.randn_like(x, device=devices.cpu).to(x.device) else: return torch.randn_like(x) diff --git a/modules/shared.py b/modules/shared.py index b5b401fe..73704889 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -334,7 +334,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "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}), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), - "use_cpu_randn": OptionInfo(False, "Use CPU for random number generation to make manual seeds generate the same image across platforms. This may change existing seeds."), + "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"]}), })) options_templates.update(options_section(('compatibility', "Compatibility"), { -- cgit v1.2.3 From 1d11e896984c883f6a0debb3abaef945595cbc70 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Apr 2023 15:57:09 +0300 Subject: rework Negative Guidance minimum sigma to work with AND, add infotext and copypaste parameters support --- javascript/hints.js | 3 ++- modules/generation_parameters_copypaste.py | 1 + modules/processing.py | 3 ++- modules/sd_samplers_kdiffusion.py | 43 +++++++++++++++++------------- 4 files changed, 30 insertions(+), 20 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/javascript/hints.js b/javascript/hints.js index c6bae360..44d418da 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -111,7 +111,8 @@ titles = { "Resize height to": "Resizes image to this height. If 0, height is inferred from either of two nearby sliders.", "Multiplier for extra networks": "When adding extra network such as Hypernetwork or Lora to prompt, use this multiplier for it.", "Discard weights with matching name": "Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.", - "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited." + "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited.", + "Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction." } diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index e7269363..99f1a0d3 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -309,6 +309,7 @@ infotext_to_setting_name_mapping = [ ('UniPC order', 'uni_pc_order'), ('UniPC lower order final', 'uni_pc_lower_order_final'), ('RNG', 'randn_source'), + ('NGMS', 's_min_uncond'), ] diff --git a/modules/processing.py b/modules/processing.py index 04a06290..c50784f4 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -480,7 +480,8 @@ 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, "Init image hash": getattr(p, 'init_img_hash', None), - "RNG": (opts.randn_source if opts.randn_source != "GPU" else 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, } generation_params.update(p.extra_generation_params) diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index d42d5fcf..f8aaac59 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -115,20 +115,21 @@ class CFGDenoiser(torch.nn.Module): sigma_in = denoiser_params.sigma tensor = denoiser_params.text_cond uncond = denoiser_params.text_uncond + skip_uncond = False - if self.step % 2 and s_min_uncond > 0 and not is_edit_model: - # alternating uncond allows for higher thresholds without the quality loss normally expected from raising it - sigma_threshold = s_min_uncond - if(torch.dot(sigma,sigma) < sigma.shape[0] * (sigma_threshold*sigma_threshold) ): - uncond = torch.zeros([0,0,uncond.shape[2]]) - x_in=x_in[:x_in.shape[0]//2] - sigma_in=sigma_in[:sigma_in.shape[0]//2] + # alternating uncond allows for higher thresholds without the quality loss normally expected from raising it + if self.step % 2 and s_min_uncond > 0 and sigma[0] < s_min_uncond and not is_edit_model: + skip_uncond = True + x_in = x_in[:-batch_size] + sigma_in = sigma_in[:-batch_size] - if tensor.shape[1] == uncond.shape[1]: - if not is_edit_model: - cond_in = torch.cat([tensor, uncond]) - else: + if tensor.shape[1] == uncond.shape[1] or skip_uncond: + if is_edit_model: cond_in = torch.cat([tensor, uncond, uncond]) + elif skip_uncond: + cond_in = tensor + else: + cond_in = torch.cat([tensor, uncond]) if shared.batch_cond_uncond: x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in)) @@ -152,9 +153,15 @@ class CFGDenoiser(torch.nn.Module): x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b])) - if uncond.shape[0]: + if not skip_uncond: x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=make_condition_dict([uncond], image_cond_in[-uncond.shape[0]:])) + if skip_uncond: + #x_out = torch.cat([x_out, x_out[0:batch_size]]) # we skipped uncond denoising, so we put cond-denoised image to where the uncond-denoised image should be + denoised_image_indexes = [x[0][0] for x in conds_list] + fake_uncond = torch.cat([x_out[i:i+1] for i in denoised_image_indexes]) + x_out = torch.cat([x_out, fake_uncond]) + denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps) cfg_denoised_callback(denoised_params) @@ -165,13 +172,12 @@ class CFGDenoiser(torch.nn.Module): elif opts.live_preview_content == "Negative prompt": sd_samplers_common.store_latent(x_out[-uncond.shape[0]:]) - if not is_edit_model: - if uncond.shape[0]: - denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale) - else: - denoised = x_out - else: + if is_edit_model: denoised = self.combine_denoised_for_edit_model(x_out, cond_scale) + elif skip_uncond: + denoised = self.combine_denoised(x_out, conds_list, uncond, 1.0) + else: + denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale) if self.mask is not None: denoised = self.init_latent * self.mask + self.nmask * denoised @@ -221,6 +227,7 @@ class KDiffusionSampler: self.eta = None self.config = None self.last_latent = None + self.s_min_uncond = None self.conditioning_key = sd_model.model.conditioning_key -- 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/generation_parameters_copypaste.py') 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 a3cdf9aaf85399d6ddfb5bc3245d8f154802fe58 Mon Sep 17 00:00:00 2001 From: Sakura-Luna <53183413+Sakura-Luna@users.noreply.github.com> Date: Fri, 5 May 2023 15:51:01 +0800 Subject: Reopen image fix --- modules/generation_parameters_copypaste.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6df76858..ae855627 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -59,6 +59,7 @@ def image_from_url_text(filedata): is_in_right_dir = ui_tempdir.check_tmp_file(shared.demo, filename) assert is_in_right_dir, 'trying to open image file outside of allowed directories' + filename = filename.rsplit('?', 1)[0] return Image.open(filename) if type(filedata) == list: -- cgit v1.2.3 From 18fb2162a44ae06eaff302845abb880f27bcc975 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 8 May 2023 12:17:36 +0300 Subject: disable useless progress display when pasting infotext using the blur button --- modules/generation_parameters_copypaste.py | 5 +++++ 1 file changed, 5 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 99f1a0d3..6cc8d13b 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -129,6 +129,7 @@ def connect_paste_params_buttons(): _js=jsfunc, inputs=[binding.source_image_component], outputs=[destination_image_component, destination_width_component, destination_height_component] if destination_width_component else [destination_image_component], + show_progress=False, ) if binding.source_text_component is not None and fields is not None: @@ -140,6 +141,7 @@ def connect_paste_params_buttons(): fn=lambda *x: x, inputs=[field for field, name in paste_fields[binding.source_tabname]["fields"] if name in paste_field_names], outputs=[field for field, name in fields if name in paste_field_names], + show_progress=False, ) binding.paste_button.click( @@ -147,6 +149,7 @@ def connect_paste_params_buttons(): _js=f"switch_to_{binding.tabname}", inputs=None, outputs=None, + show_progress=False, ) @@ -409,12 +412,14 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, fn=paste_func, inputs=[input_comp], outputs=[x[0] for x in paste_fields], + show_progress=False, ) button.click( fn=None, _js=f"recalculate_prompts_{tabname}", inputs=[], outputs=[], + show_progress=False, ) -- cgit v1.2.3 From 3ba6c3c83c0983a025c7bddc08bb7f49481b3cbb Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Tue, 9 May 2023 22:17:58 +0300 Subject: Fix up string formatting/concatenation to f-strings where feasible --- modules/api/api.py | 22 ++++++------ modules/call_queue.py | 5 +-- modules/esrgan_model.py | 11 +++--- modules/esrgan_model_arch.py | 16 ++++----- modules/extra_networks_hypernet.py | 3 +- modules/generation_parameters_copypaste.py | 4 +-- modules/hashes.py | 4 +-- modules/images.py | 8 ++--- modules/interrogate.py | 4 +-- modules/models/diffusion/ddpm_edit.py | 4 +-- modules/models/diffusion/uni_pc/uni_pc.py | 4 +-- modules/ngrok.py | 4 +-- modules/paths.py | 2 +- modules/processing.py | 13 ++++++-- modules/progress.py | 3 +- modules/realesrgan_model.py | 8 ++--- modules/scripts.py | 5 +-- modules/sd_hijack_clip_old.py | 3 +- modules/sd_hijack_unet.py | 2 +- modules/sd_models.py | 4 +-- modules/sd_models_config.py | 2 +- modules/sd_samplers_kdiffusion.py | 2 +- modules/sd_vae.py | 2 +- modules/styles.py | 2 +- modules/textual_inversion/autocrop.py | 6 ++-- modules/textual_inversion/dataset.py | 2 +- modules/textual_inversion/preprocess.py | 6 ++-- modules/textual_inversion/textual_inversion.py | 12 +++---- modules/ui.py | 46 +++++++++++++------------- modules/ui_extensions.py | 3 +- modules/ui_extra_networks.py | 4 ++- scripts/custom_code.py | 2 +- scripts/loopback.py | 2 +- scripts/xyz_grid.py | 2 +- 34 files changed, 121 insertions(+), 101 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/api/api.py b/modules/api/api.py index cdbdce32..9bb95dfd 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -570,20 +570,20 @@ 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 = "create embedding filename: {filename}".format(filename = filename)) + return CreateResponse(info=f"create embedding filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info = "create embedding error: {error}".format(error = e)) + return 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 = "create hypernetwork filename: {filename}".format(filename = filename)) + return CreateResponse(info=f"create hypernetwork filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info = "create hypernetwork error: {error}".format(error = e)) + return TrainResponse(info=f"create hypernetwork error: {e}") def preprocess(self, args: dict): try: @@ -593,13 +593,13 @@ class Api: return PreprocessResponse(info = 'preprocess complete') except KeyError as e: shared.state.end() - return PreprocessResponse(info = "preprocess error: invalid token: {error}".format(error = e)) + return PreprocessResponse(info=f"preprocess error: invalid token: {e}") except AssertionError as e: shared.state.end() - return PreprocessResponse(info = "preprocess error: {error}".format(error = e)) + return PreprocessResponse(info=f"preprocess error: {e}") except FileNotFoundError as e: shared.state.end() - return PreprocessResponse(info = 'preprocess error: {error}'.format(error = e)) + return PreprocessResponse(info=f'preprocess error: {e}') def train_embedding(self, args: dict): try: @@ -617,10 +617,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error)) + return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info = "train embedding error: {msg}".format(msg = msg)) + return TrainResponse(info=f"train embedding error: {msg}") def train_hypernetwork(self, args: dict): try: @@ -641,10 +641,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error)) + return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info="train embedding error: {error}".format(error=error)) + return TrainResponse(info=f"train embedding error: {error}") def get_memory(self): try: diff --git a/modules/call_queue.py b/modules/call_queue.py index 1829f3a6..447bb764 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -60,7 +60,7 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): max_debug_str_len = 131072 # (1024*1024)/8 print("Error completing request", file=sys.stderr) - argStr = f"Arguments: {str(args)} {str(kwargs)}" + argStr = f"Arguments: {args} {kwargs}" print(argStr[:max_debug_str_len], file=sys.stderr) if len(argStr) > max_debug_str_len: print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr) @@ -73,7 +73,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): if extra_outputs_array is None: extra_outputs_array = [None, ''] - res = extra_outputs_array + [f"
{html.escape(type(e).__name__+': '+str(e))}
"] + error_message = f'{type(e).__name__}: {e}' + res = extra_outputs_array + [f"
{html.escape(error_message)}
"] shared.state.skipped = False shared.state.interrupted = False diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 9a9c38f1..f4369257 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -156,13 +156,16 @@ class UpscalerESRGAN(Upscaler): def load_model(self, path: str): if "http" in path: - filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, - file_name="%s.pth" % self.model_name, - progress=True) + filename = load_file_from_url( + url=self.model_url, + model_dir=self.model_path, + file_name=f"{self.model_name}.pth", + progress=True, + ) else: filename = path if not os.path.exists(filename) or filename is None: - print("Unable to load %s from %s" % (self.model_path, filename)) + print(f"Unable to load {self.model_path} from {filename}") return None state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None) diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 1b52b0f5..6071fea7 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -38,7 +38,7 @@ class RRDBNet(nn.Module): elif upsample_mode == 'pixelshuffle': upsample_block = pixelshuffle_block else: - raise NotImplementedError('upsample mode [{:s}] is not found'.format(upsample_mode)) + raise NotImplementedError(f'upsample mode [{upsample_mode}] is not found') if upscale == 3: upsampler = upsample_block(nf, nf, 3, act_type=act_type, convtype=convtype) else: @@ -261,10 +261,10 @@ class Upsample(nn.Module): def extra_repr(self): if self.scale_factor is not None: - info = 'scale_factor=' + str(self.scale_factor) + info = f'scale_factor={self.scale_factor}' else: - info = 'size=' + str(self.size) - info += ', mode=' + self.mode + info = f'size={self.size}' + info += f', mode={self.mode}' return info @@ -350,7 +350,7 @@ def act(act_type, inplace=True, neg_slope=0.2, n_prelu=1, beta=1.0): elif act_type == 'sigmoid': # [0, 1] range output layer = nn.Sigmoid() else: - raise NotImplementedError('activation layer [{:s}] is not found'.format(act_type)) + raise NotImplementedError(f'activation layer [{act_type}] is not found') return layer @@ -372,7 +372,7 @@ def norm(norm_type, nc): elif norm_type == 'none': def norm_layer(x): return Identity() else: - raise NotImplementedError('normalization layer [{:s}] is not found'.format(norm_type)) + raise NotImplementedError(f'normalization layer [{norm_type}] is not found') return layer @@ -388,7 +388,7 @@ def pad(pad_type, padding): elif pad_type == 'zero': layer = nn.ZeroPad2d(padding) else: - raise NotImplementedError('padding layer [{:s}] is not implemented'.format(pad_type)) + raise NotImplementedError(f'padding layer [{pad_type}] is not implemented') return layer @@ -432,7 +432,7 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias= pad_type='zero', norm_type=None, act_type='relu', mode='CNA', convtype='Conv2D', spectral_norm=False): """ Conv layer with padding, normalization, activation """ - assert mode in ['CNA', 'NAC', 'CNAC'], 'Wrong conv mode [{:s}]'.format(mode) + assert mode in ['CNA', 'NAC', 'CNAC'], f'Wrong conv mode [{mode}]' padding = get_valid_padding(kernel_size, dilation) p = pad(pad_type, padding) if pad_type and pad_type != 'zero' else None padding = padding if pad_type == 'zero' else 0 diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index 33d100dd..04f27c9f 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -10,7 +10,8 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): additional = shared.opts.sd_hypernetwork if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0: - p.all_prompts = [x + f"" for x in p.all_prompts] + hypernet_prompt_text = f"" + p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts] params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier])) names = [] diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 78248ed2..fe8b18b2 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -269,8 +269,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v m = re_imagesize.match(v) if m is not None: - res[k+"-1"] = m.group(1) - res[k+"-2"] = m.group(2) + res[f"{k}-1"] = m.group(1) + res[f"{k}-2"] = m.group(2) else: res[k] = v diff --git a/modules/hashes.py b/modules/hashes.py index 83272a07..032120f4 100644 --- a/modules/hashes.py +++ b/modules/hashes.py @@ -13,7 +13,7 @@ cache_data = None def dump_cache(): - with filelock.FileLock(cache_filename+".lock"): + with filelock.FileLock(f"{cache_filename}.lock"): with open(cache_filename, "w", encoding="utf8") as file: json.dump(cache_data, file, indent=4) @@ -22,7 +22,7 @@ def cache(subsection): global cache_data if cache_data is None: - with filelock.FileLock(cache_filename+".lock"): + with filelock.FileLock(f"{cache_filename}.lock"): if not os.path.isfile(cache_filename): cache_data = {} else: diff --git a/modules/images.py b/modules/images.py index 6ceb7c7c..a41965ab 100644 --- a/modules/images.py +++ b/modules/images.py @@ -467,7 +467,7 @@ def get_next_sequence_number(path, basename): """ result = -1 if basename != '': - basename = basename + "-" + basename = f"{basename}-" prefix_length = len(basename) for p in os.listdir(path): @@ -536,7 +536,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i add_number = opts.save_images_add_number or file_decoration == '' if file_decoration != "" and add_number: - file_decoration = "-" + file_decoration + file_decoration = f"-{file_decoration}" file_decoration = namegen.apply(file_decoration) + suffix @@ -566,7 +566,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i def _atomically_save_image(image_to_save, filename_without_extension, extension): # save image with .tmp extension to avoid race condition when another process detects new image in the directory - temp_file_path = filename_without_extension + ".tmp" + temp_file_path = f"{filename_without_extension}.tmp" image_format = Image.registered_extensions()[extension] if extension.lower() == '.png': @@ -626,7 +626,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i if opts.save_txt and info is not None: txt_fullfn = f"{fullfn_without_extension}.txt" with open(txt_fullfn, "w", encoding="utf8") as file: - file.write(info + "\n") + file.write(f"{info}\n") else: txt_fullfn = None diff --git a/modules/interrogate.py b/modules/interrogate.py index e1665708..9f7d657f 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -28,7 +28,7 @@ def category_types(): def download_default_clip_interrogate_categories(content_dir): print("Downloading CLIP categories...") - tmpdir = content_dir + "_tmp" + tmpdir = f"{content_dir}_tmp" category_types = ["artists", "flavors", "mediums", "movements"] try: @@ -214,7 +214,7 @@ class InterrogateModels: if shared.opts.interrogate_return_ranks: res += f", ({match}:{score/100:.3f})" else: - res += ", " + match + res += f", {match}" except Exception: print("Error interrogating", file=sys.stderr) diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index f3d49c44..f880bc3c 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -223,7 +223,7 @@ class DDPM(pl.LightningModule): for k in keys: for ik in ignore_keys: if k.startswith(ik): - print("Deleting key {} from state_dict.".format(k)) + print(f"Deleting key {k} from state_dict.") del sd[k] missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) @@ -386,7 +386,7 @@ class DDPM(pl.LightningModule): _, loss_dict_no_ema = self.shared_step(batch) with self.ema_scope(): _, loss_dict_ema = self.shared_step(batch) - loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema} + loss_dict_ema = {f"{key}_ema": loss_dict_ema[key] for key in loss_dict_ema} self.log_dict(loss_dict_no_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) self.log_dict(loss_dict_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index eb5f4e76..11b330bc 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -94,7 +94,7 @@ class NoiseScheduleVP: """ if schedule not in ['discrete', 'linear', 'cosine']: - raise ValueError("Unsupported noise schedule {}. The schedule needs to be 'discrete' or 'linear' or 'cosine'".format(schedule)) + raise ValueError(f"Unsupported noise schedule {schedule}. The schedule needs to be 'discrete' or 'linear' or 'cosine'") self.schedule = schedule if schedule == 'discrete': @@ -469,7 +469,7 @@ class UniPC: t = torch.linspace(t_T**(1. / t_order), t_0**(1. / t_order), N + 1).pow(t_order).to(device) return t else: - raise ValueError("Unsupported skip_type {}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'".format(skip_type)) + raise ValueError(f"Unsupported skip_type {skip_type}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'") def get_orders_and_timesteps_for_singlestep_solver(self, steps, order, skip_type, t_T, t_0, device): """ diff --git a/modules/ngrok.py b/modules/ngrok.py index 1ad7989b..7a7b4b26 100644 --- a/modules/ngrok.py +++ b/modules/ngrok.py @@ -7,8 +7,8 @@ def connect(token, port, region): else: if ':' in token: # token = authtoken:username:password - account = token.split(':')[1] + ':' + token.split(':')[-1] - token = token.split(':')[0] + token, username, password = token.split(':', 2) + account = f"{username}:{password}" config = conf.PyngrokConfig( auth_token=token, region=region diff --git a/modules/paths.py b/modules/paths.py index 0e1e00e7..acf1894b 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -16,7 +16,7 @@ for possible_sd_path in possible_sd_paths: sd_path = os.path.abspath(possible_sd_path) break -assert sd_path is not None, "Couldn't find Stable Diffusion in any of: " + str(possible_sd_paths) +assert sd_path is not None, f"Couldn't find Stable Diffusion in any of: {possible_sd_paths}" path_dirs = [ (sd_path, 'ldm', 'Stable Diffusion', []), diff --git a/modules/processing.py b/modules/processing.py index e786791a..1a76e552 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -500,7 +500,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter 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 = "\nNegative prompt: " + p.all_negative_prompts[index] if p.all_negative_prompts[index] else "" + negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else "" return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() @@ -780,7 +780,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: devices.torch_gc() - res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts) + res = Processed( + p, + images_list=output_images, + seed=p.all_seeds[0], + info=infotext(), + comments="".join(f"\n\n{comment}" for comment in comments), + subseed=p.all_subseeds[0], + index_of_first_image=index_of_first_image, + infotexts=infotexts, + ) if p.scripts is not None: p.scripts.postprocess(p, res) diff --git a/modules/progress.py b/modules/progress.py index 5655346b..948e6f00 100644 --- a/modules/progress.py +++ b/modules/progress.py @@ -96,7 +96,8 @@ def progressapi(req: ProgressRequest): if image is not None: buffered = io.BytesIO() image.save(buffered, format="png") - live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii") + base64_image = base64.b64encode(buffered.getvalue()).decode('ascii') + live_preview = f"data:image/png;base64,{base64_image}" id_live_preview = shared.state.id_live_preview else: live_preview = None diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index d6079433..efd7fca5 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -28,9 +28,9 @@ class UpscalerRealESRGAN(Upscaler): for scaler in scalers: if scaler.local_data_path.startswith("http"): filename = modelloader.friendly_name(scaler.local_data_path) - local = next(iter([local_model for local_model in local_model_paths if local_model.endswith(filename + '.pth')]), None) - if local: - scaler.local_data_path = local + local_model_candidates = [local_model for local_model in local_model_paths if local_model.endswith(f"{filename}.pth")] + if local_model_candidates: + scaler.local_data_path = local_model_candidates[0] if scaler.name in opts.realesrgan_enabled_models: self.scalers.append(scaler) @@ -47,7 +47,7 @@ class UpscalerRealESRGAN(Upscaler): info = self.load_model(path) if not os.path.exists(info.local_data_path): - print("Unable to load RealESRGAN model: %s" % info.name) + print(f"Unable to load RealESRGAN model: {info.name}") return img upsampler = RealESRGANer( diff --git a/modules/scripts.py b/modules/scripts.py index 4d0bbd66..d945b89f 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -163,7 +163,8 @@ class Script: """helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id""" need_tabname = self.show(True) == self.show(False) - tabname = ('img2img' if self.is_img2img else 'txt2txt') + "_" if need_tabname else "" + tabkind = 'img2img' if self.is_img2img else 'txt2txt' + tabname = f"{tabkind}_" if need_tabname else "" title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower())) return f'script_{tabname}{title}_{item_id}' @@ -526,7 +527,7 @@ def add_classes_to_gradio_component(comp): this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others """ - comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])] + comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] if getattr(comp, 'multiselect', False): comp.elem_classes.append('multiselect') diff --git a/modules/sd_hijack_clip_old.py b/modules/sd_hijack_clip_old.py index 6d9fbbe6..a3476e95 100644 --- a/modules/sd_hijack_clip_old.py +++ b/modules/sd_hijack_clip_old.py @@ -75,7 +75,8 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text self.hijack.comments += hijack_comments if len(used_custom_terms) > 0: - self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) + embedding_names = ", ".join(f"{word} [{checksum}]" for word, checksum in used_custom_terms) + self.hijack.comments.append(f"Used embeddings: {embedding_names}") self.hijack.fixes = hijack_fixes return self.process_tokens(remade_batch_tokens, batch_multipliers) diff --git a/modules/sd_hijack_unet.py b/modules/sd_hijack_unet.py index 15858263..ca1daf45 100644 --- a/modules/sd_hijack_unet.py +++ b/modules/sd_hijack_unet.py @@ -18,7 +18,7 @@ class TorchHijackForUnet: if hasattr(torch, item): return getattr(torch, item) - raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item)) + raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'") def cat(self, tensors, *args, **kwargs): if len(tensors) == 2: diff --git a/modules/sd_models.py b/modules/sd_models.py index 59adc7cc..36f643e1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -47,7 +47,7 @@ class CheckpointInfo: self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0] self.hash = model_hash(filename) - self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + name) + self.sha256 = hashes.sha256_from_cache(self.filename, f"checkpoint/{name}") self.shorthash = self.sha256[0:10] if self.sha256 else None self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' @@ -69,7 +69,7 @@ class CheckpointInfo: checkpoint_alisases[id] = self def calculate_shorthash(self): - self.sha256 = hashes.sha256(self.filename, "checkpoint/" + self.name) + self.sha256 = hashes.sha256(self.filename, f"checkpoint/{self.name}") if self.sha256 is None: return diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 9398f528..7a79925a 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -111,7 +111,7 @@ def find_checkpoint_config_near_filename(info): if info is None: return None - config = os.path.splitext(info.filename)[0] + ".yaml" + config = f"{os.path.splitext(info.filename)[0]}.yaml" if os.path.exists(config): return config diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index eb98e599..0fc9f456 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -198,7 +198,7 @@ class TorchHijack: if hasattr(torch, item): return getattr(torch, item) - raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item)) + raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'") def randn_like(self, x): if self.sampler_noises: diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 9b00f76e..521e485a 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -89,7 +89,7 @@ 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"]: + for vae_location in [f"{checkpoint_path}.vae.pt", f"{checkpoint_path}.vae.ckpt", f"{checkpoint_path}.vae.safetensors"]: if os.path.isfile(vae_location): return vae_location diff --git a/modules/styles.py b/modules/styles.py index 9ed85991..11642075 100644 --- a/modules/styles.py +++ b/modules/styles.py @@ -74,7 +74,7 @@ class StyleDatabase: def save_styles(self, path: str) -> None: # Always keep a backup file around if os.path.exists(path): - shutil.copy(path, path + ".bak") + shutil.copy(path, f"{path}.bak") fd = os.open(path, os.O_RDWR|os.O_CREAT) with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file: diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 68e1103c..ba1bdcd4 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -111,7 +111,7 @@ def focal_point(im, settings): if corner_centroid is not None: color = BLUE box = corner_centroid.bounding(max_size * corner_centroid.weight) - d.text((box[0], box[1]-15), "Edge: %.02f" % corner_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Edge: {corner_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(corner_points) > 1: for f in corner_points: @@ -119,7 +119,7 @@ def focal_point(im, settings): if entropy_centroid is not None: color = "#ff0" box = entropy_centroid.bounding(max_size * entropy_centroid.weight) - d.text((box[0], box[1]-15), "Entropy: %.02f" % entropy_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(entropy_points) > 1: for f in entropy_points: @@ -127,7 +127,7 @@ def focal_point(im, settings): if face_centroid is not None: color = RED box = face_centroid.bounding(max_size * face_centroid.weight) - d.text((box[0], box[1]-15), "Face: %.02f" % face_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Face: {face_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(face_points) > 1: for f in face_points: diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index af9fbcf2..41610e03 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -72,7 +72,7 @@ class PersonalizedBase(Dataset): except Exception: continue - text_filename = os.path.splitext(path)[0] + ".txt" + text_filename = f"{os.path.splitext(path)[0]}.txt" filename = os.path.basename(path) if os.path.exists(text_filename): diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 4a29151d..da0bcb26 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -63,9 +63,9 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti image.save(os.path.join(params.dstdir, f"{basename}.png")) if params.preprocess_txt_action == 'prepend' and existing_caption: - caption = existing_caption + ' ' + caption + caption = f"{existing_caption} {caption}" elif params.preprocess_txt_action == 'append' and existing_caption: - caption = caption + ' ' + existing_caption + caption = f"{caption} {existing_caption}" elif params.preprocess_txt_action == 'copy' and existing_caption: caption = existing_caption @@ -174,7 +174,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre params.src = filename existing_caption = None - existing_caption_filename = os.path.splitext(filename)[0] + '.txt' + existing_caption_filename = f"{os.path.splitext(filename)[0]}.txt" if os.path.exists(existing_caption_filename): with open(existing_caption_filename, 'r', encoding="utf8") as file: existing_caption = file.read() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 379df243..4368eb63 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -69,7 +69,7 @@ class Embedding: 'hash': self.checksum(), 'optimizer_state_dict': self.optimizer_state_dict, } - torch.save(optimizer_saved_dict, filename + '.optim') + torch.save(optimizer_saved_dict, f"{filename}.optim") def checksum(self): if self.cached_checksum is not None: @@ -437,8 +437,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate, weight_decay=0.0) if shared.opts.save_optimizer_state: optimizer_state_dict = None - if os.path.exists(filename + '.optim'): - optimizer_saved_dict = torch.load(filename + '.optim', map_location='cpu') + if os.path.exists(f"{filename}.optim"): + 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) @@ -599,7 +599,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st data = torch.load(last_saved_file) info.add_text("sd-ti-embedding", embedding_to_b64(data)) - title = "<{}>".format(data.get('name', '???')) + title = f"<{data.get('name', '???')}>" try: vectorSize = list(data['string_to_param'].values())[0].shape[0] @@ -608,8 +608,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st checkpoint = sd_models.select_checkpoint() footer_left = checkpoint.model_name - footer_mid = '[{}]'.format(checkpoint.shorthash) - footer_right = '{}v {}s'.format(vectorSize, steps_done) + footer_mid = f'[{checkpoint.shorthash}]' + footer_right = f'{vectorSize}v {steps_done}s' captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right) captioned_image = insert_image_data_embed(captioned_image, data) diff --git a/modules/ui.py b/modules/ui.py index 34b2aaff..d02f6e82 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -101,7 +101,7 @@ def visit(x, func, path=""): for c in x.children: visit(c, func, path) elif x.label is not None: - func(path + "/" + str(x.label), x) + func(f"{path}/{x.label}", x) def add_style(name: str, prompt: str, negative_prompt: str): @@ -166,7 +166,7 @@ def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_di img = Image.open(image) filename = os.path.basename(image) left, _ = os.path.splitext(filename) - print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a')) + print(interrogation_function(img), file=open(os.path.join(ii_output_dir, f"{left}.txt"), 'a')) return [gr.update(), None] @@ -182,29 +182,29 @@ def interrogate_deepbooru(image): def create_seed_inputs(target_interface): - with FormRow(elem_id=target_interface + '_seed_row', variant="compact"): - seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed') + with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"): + seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=f"{target_interface}_seed") seed.style(container=False) - random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed', label='Random seed') - reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed', label='Reuse seed') + random_seed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_seed", label='Random seed') + reuse_seed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_seed", label='Reuse seed') - seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False) + seed_checkbox = gr.Checkbox(label='Extra', elem_id=f"{target_interface}_subseed_show", value=False) # Components to show/hide based on the 'Extra' checkbox seed_extras = [] - with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1: + with FormRow(visible=False, elem_id=f"{target_interface}_subseed_row") as seed_extra_row_1: seed_extras.append(seed_extra_row_1) - subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed') + subseed = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed") subseed.style(container=False) - random_subseed = ToolButton(random_symbol, elem_id=target_interface + '_random_subseed') - reuse_subseed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_subseed') - subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength') + random_subseed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_subseed") + reuse_subseed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_subseed") + subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=f"{target_interface}_subseed_strength") with FormRow(visible=False) as seed_extra_row_2: seed_extras.append(seed_extra_row_2) - seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w') - seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h') + seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=f"{target_interface}_seed_resize_from_w") + seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=f"{target_interface}_seed_resize_from_h") random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed]) random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed]) @@ -765,7 +765,7 @@ def create_ui(): ) button.click( fn=lambda: None, - _js="switch_to_"+name.replace(" ", "_"), + _js=f"switch_to_{name.replace(' ', '_')}", inputs=[], outputs=[], ) @@ -1462,18 +1462,18 @@ def create_ui(): elif t == bool: comp = gr.Checkbox else: - raise Exception(f'bad options item type: {str(t)} for key {key}') + raise Exception(f'bad options item type: {t} for key {key}') - elem_id = "setting_"+key + elem_id = f"setting_{key}" if info.refresh is not None: if is_quicksettings: res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) - create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}") else: with FormRow(): res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) - create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}") else: res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) @@ -1545,7 +1545,7 @@ def create_ui(): current_tab.__exit__() gr.Group() - current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text) + current_tab = gr.TabItem(elem_id=f"settings_{elem_id}", label=text) current_tab.__enter__() current_row = gr.Column(variant='compact') current_row.__enter__() @@ -1664,7 +1664,7 @@ def create_ui(): for interface, label, ifid in interfaces: if label in shared.opts.hidden_tabs: continue - with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid): + with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"): interface.render() if os.path.exists(os.path.join(script_path, "notification.mp3")): @@ -1771,10 +1771,10 @@ def create_ui(): def loadsave(path, x): def apply_field(obj, field, condition=None, init_field=None): - key = path + "/" + field + key = f"{path}/{field}" if getattr(obj, 'custom_script_source', None) is not None: - key = 'customscript/' + obj.custom_script_source + '/' + key + key = f"customscript/{obj.custom_script_source}/{key}" if getattr(obj, 'do_not_save_to_config', False): return diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 99ac8756..d9faf85a 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -61,7 +61,8 @@ def save_config_state(name): if not name: name = "Config" current_config_state["name"] = name - filename = os.path.join(config_states_dir, datetime.now().strftime("%Y_%m_%d-%H_%M_%S") + "_" + name + ".json") + timestamp = datetime.now().strftime('%Y_%m_%d-%H_%M_%S') + filename = os.path.join(config_states_dir, f"{timestamp}_{name}.json") print(f"Saving backup of webui/extension state to {filename}.") with open(filename, "w", encoding="utf-8") as f: json.dump(current_config_state, f) diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 86c05a55..8c3dea56 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -69,7 +69,9 @@ class ExtraNetworksPage: pass def link_preview(self, filename): - return "./sd_extra_networks/thumb?filename=" + urllib.parse.quote(filename.replace('\\', '/')) + "&mtime=" + str(os.path.getmtime(filename)) + quoted_filename = urllib.parse.quote(filename.replace('\\', '/')) + mtime = os.path.getmtime(filename) + return f"./sd_extra_networks/thumb?filename={quoted_filename}&mtime={mtime}" def search_terms_from_path(self, filename, possible_directories=None): abspath = os.path.abspath(filename) diff --git a/scripts/custom_code.py b/scripts/custom_code.py index 4071d86d..f36a3675 100644 --- a/scripts/custom_code.py +++ b/scripts/custom_code.py @@ -77,7 +77,7 @@ return process_images(p) module.display = display indent = " " * indent_level - indented = code.replace('\n', '\n' + indent) + indented = code.replace('\n', f"\n{indent}") body = f"""def __webuitemp__(): {indent}{indented} __webuitemp__()""" diff --git a/scripts/loopback.py b/scripts/loopback.py index d3065fe6..ad6609be 100644 --- a/scripts/loopback.py +++ b/scripts/loopback.py @@ -84,7 +84,7 @@ class Script(scripts.Script): p.color_corrections = initial_color_corrections if append_interrogation != "None": - p.prompt = original_prompt + ", " if original_prompt != "" else "" + p.prompt = f"{original_prompt}, " if original_prompt else "" if append_interrogation == "CLIP": p.prompt += shared.interrogator.interrogate(p.init_images[0]) elif append_interrogation == "DeepBooru": diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 01d97791..a725d74a 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -439,7 +439,7 @@ class Script(scripts.Script): z_type.change(fn=select_axis, inputs=[z_type,z_values_dropdown], outputs=[fill_z_button,z_values,z_values_dropdown]) def get_dropdown_update_from_params(axis,params): - val_key = axis + " Values" + val_key = f"{axis} Values" vals = params.get(val_key,"") valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x] return gr.update(value = valslist) -- 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 --- extensions-builtin/Lora/lora.py | 1 - extensions-builtin/ScuNET/scripts/scunet_model.py | 1 - extensions-builtin/SwinIR/scripts/swinir_model.py | 3 +-- 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 +- pyproject.toml | 11 +++++++---- scripts/custom_code.py | 2 +- scripts/outpainting_mk_2.py | 4 ++-- scripts/poor_mans_outpainting.py | 4 ++-- scripts/prompt_matrix.py | 7 ++----- scripts/prompts_from_file.py | 5 +---- scripts/sd_upscale.py | 4 ++-- scripts/xyz_grid.py | 6 ++---- webui.py | 2 +- 48 files changed, 42 insertions(+), 114 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index ba1293df..0ab43229 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -1,4 +1,3 @@ -import glob import os import re import torch diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index c7fd5739..aa2fdb3a 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -13,7 +13,6 @@ import modules.upscaler from modules import devices, modelloader from scunet_model_arch import SCUNet as net from modules.shared import opts -from modules import images class UpscalerScuNET(modules.upscaler.Upscaler): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index d77c3a92..55dd94ab 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -1,4 +1,3 @@ -import contextlib import os import numpy as np @@ -8,7 +7,7 @@ from basicsr.utils.download_util import load_file_from_url from tqdm import tqdm from modules import modelloader, devices, script_callbacks, shared -from modules.shared import cmd_opts, opts, state +from modules.shared import opts, state from swinir_model_arch import SwinIR as net from swinir_model_arch_v2 import Swin2SR as net2 from modules.upscaler import Upscaler, UpscalerData 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 diff --git a/pyproject.toml b/pyproject.toml index 1e164abc..9caa9ba2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,10 +1,13 @@ [tool.ruff] +exclude = ["extensions"] + ignore = [ "E501", - "E731", - "E402", # Module level import not at top of file - "F401" # Module imported but unused + + "F401", # Module imported but unused ] -exclude = ["extensions"] + +[tool.ruff.per-file-ignores] +"webui.py" = ["E402"] # Module level import not at top of file \ No newline at end of file diff --git a/scripts/custom_code.py b/scripts/custom_code.py index f36a3675..cc6f0d49 100644 --- a/scripts/custom_code.py +++ b/scripts/custom_code.py @@ -4,7 +4,7 @@ import ast import copy from modules.processing import Processed -from modules.shared import opts, cmd_opts, state +from modules.shared import cmd_opts def convertExpr2Expression(expr): diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index b10fed6c..665dbe89 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -7,9 +7,9 @@ import modules.scripts as scripts import gradio as gr from PIL import Image, ImageDraw -from modules import images, processing, devices +from modules import images from modules.processing import Processed, process_images -from modules.shared import opts, cmd_opts, state +from modules.shared import opts, state # this function is taken from https://github.com/parlance-zz/g-diffuser-bot diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py index ddcbd2d3..c0bbecc1 100644 --- a/scripts/poor_mans_outpainting.py +++ b/scripts/poor_mans_outpainting.py @@ -4,9 +4,9 @@ import modules.scripts as scripts import gradio as gr from PIL import Image, ImageDraw -from modules import images, processing, devices +from modules import images, devices from modules.processing import Processed, process_images -from modules.shared import opts, cmd_opts, state +from modules.shared import opts, state class Script(scripts.Script): diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py index e9b11517..fb06beab 100644 --- a/scripts/prompt_matrix.py +++ b/scripts/prompt_matrix.py @@ -1,14 +1,11 @@ import math -from collections import namedtuple -from copy import copy -import random import modules.scripts as scripts import gradio as gr from modules import images -from modules.processing import process_images, Processed -from modules.shared import opts, cmd_opts, state +from modules.processing import process_images +from modules.shared import opts, state import modules.sd_samplers diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 76dc5778..149bc85f 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -1,6 +1,4 @@ import copy -import math -import os import random import sys import traceback @@ -11,8 +9,7 @@ import gradio as gr from modules import sd_samplers from modules.processing import Processed, process_images -from PIL import Image -from modules.shared import opts, cmd_opts, state +from modules.shared import state def process_string_tag(tag): diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index 332d76d9..d873a09c 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -4,9 +4,9 @@ import modules.scripts as scripts import gradio as gr from PIL import Image -from modules import processing, shared, sd_samplers, images, devices +from modules import processing, shared, images, devices from modules.processing import Processed -from modules.shared import opts, cmd_opts, state +from modules.shared import opts, state class Script(scripts.Script): diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 2ff42ef8..332e0ecd 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -10,15 +10,13 @@ import numpy as np import modules.scripts as scripts import gradio as gr -from modules import images, paths, sd_samplers, processing, sd_models, sd_vae +from modules import images, sd_samplers, processing, sd_models, sd_vae from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img -from modules.shared import opts, cmd_opts, state +from modules.shared import opts, state import modules.shared as shared import modules.sd_samplers import modules.sd_models import modules.sd_vae -import glob -import os import re from modules.ui_components import ToolButton diff --git a/webui.py b/webui.py index ec3d2aba..48277075 100644 --- a/webui.py +++ b/webui.py @@ -43,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__: torch.__long_version__ = torch.__version__ torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) -from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states +from modules import shared, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states import modules.codeformer_model as codeformer import modules.face_restoration import modules.gfpgan_model as gfpgan -- 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 --- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 10 +++++----- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 14 +++++++------- extensions-builtin/SwinIR/swinir_model_arch.py | 6 +++++- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 11 +++++++++-- 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 ++-- pyproject.toml | 5 ++++- 15 files changed, 69 insertions(+), 41 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index f457ca93..8cc82d54 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -24,7 +24,7 @@ class VQModel(pl.LightningModule): n_embed, embed_dim, ckpt_path=None, - ignore_keys=[], + ignore_keys=None, image_key="image", colorize_nlabels=None, monitor=None, @@ -62,7 +62,7 @@ class VQModel(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) + self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys or []) self.scheduler_config = scheduler_config self.lr_g_factor = lr_g_factor @@ -81,11 +81,11 @@ class VQModel(pl.LightningModule): if context is not None: print(f"{context}: Restored training weights") - def init_from_ckpt(self, path, ignore_keys=list()): + def init_from_ckpt(self, path, ignore_keys=None): sd = torch.load(path, map_location="cpu")["state_dict"] keys = list(sd.keys()) for k in keys: - for ik in ignore_keys: + for ik in ignore_keys or []: if k.startswith(ik): print("Deleting key {} from state_dict.".format(k)) del sd[k] @@ -270,7 +270,7 @@ class VQModel(pl.LightningModule): class VQModelInterface(VQModel): def __init__(self, embed_dim, *args, **kwargs): - super().__init__(embed_dim=embed_dim, *args, **kwargs) + super().__init__(*args, embed_dim=embed_dim, **kwargs) self.embed_dim = embed_dim def encode(self, x): diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index d8fc30e3..f16d6504 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -48,7 +48,7 @@ class DDPMV1(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, @@ -100,7 +100,7 @@ class DDPMV1(pl.LightningModule): if monitor is not None: self.monitor = monitor 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) self.register_schedule(given_betas=given_betas, beta_schedule=beta_schedule, timesteps=timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=cosine_s) @@ -182,13 +182,13 @@ class DDPMV1(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): sd = torch.load(path, map_location="cpu") if "state_dict" in list(sd.keys()): sd = sd["state_dict"] keys = list(sd.keys()) for k in keys: - for ik in ignore_keys: + for ik in ignore_keys or []: if k.startswith(ik): print("Deleting key {} from state_dict.".format(k)) del sd[k] @@ -444,7 +444,7 @@ class LatentDiffusionV1(DDPMV1): conditioning_key = None ckpt_path = kwargs.pop("ckpt_path", None) ignore_keys = kwargs.pop("ignore_keys", []) - super().__init__(conditioning_key=conditioning_key, *args, **kwargs) + super().__init__(*args, conditioning_key=conditioning_key, **kwargs) self.concat_mode = concat_mode self.cond_stage_trainable = cond_stage_trainable self.cond_stage_key = cond_stage_key @@ -1418,10 +1418,10 @@ class Layout2ImgDiffusionV1(LatentDiffusionV1): # 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/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 863f42db..75f7bedc 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -644,13 +644,17 @@ class SwinIR(nn.Module): """ def __init__(self, img_size=64, patch_size=1, in_chans=3, - embed_dim=96, depths=[6, 6, 6, 6], num_heads=[6, 6, 6, 6], + embed_dim=96, depths=None, num_heads=None, window_size=7, mlp_ratio=4., qkv_bias=True, qk_scale=None, drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1, norm_layer=nn.LayerNorm, ape=False, patch_norm=True, use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv', **kwargs): super(SwinIR, self).__init__() + + depths = depths or [6, 6, 6, 6] + num_heads = num_heads or [6, 6, 6, 6] + num_in_ch = in_chans num_out_ch = in_chans num_feat = 64 diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index 0e28ae6e..d4c0b0da 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -74,9 +74,12 @@ class WindowAttention(nn.Module): """ def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_drop=0., proj_drop=0., - pretrained_window_size=[0, 0]): + pretrained_window_size=None): super().__init__() + + pretrained_window_size = pretrained_window_size or [0, 0] + self.dim = dim self.window_size = window_size # Wh, Ww self.pretrained_window_size = pretrained_window_size @@ -698,13 +701,17 @@ class Swin2SR(nn.Module): """ def __init__(self, img_size=64, patch_size=1, in_chans=3, - embed_dim=96, depths=[6, 6, 6, 6], num_heads=[6, 6, 6, 6], + embed_dim=96, depths=None, num_heads=None, window_size=7, mlp_ratio=4., qkv_bias=True, drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1, norm_layer=nn.LayerNorm, ape=False, patch_norm=True, use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv', **kwargs): super(Swin2SR, self).__init__() + + depths = depths or [6, 6, 6, 6] + num_heads = num_heads or [6, 6, 6, 6] + num_in_ch = in_chans num_out_ch = in_chans num_feat = 64 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): diff --git a/pyproject.toml b/pyproject.toml index 2f65fd6c..346a0cde 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,6 +24,9 @@ ignore = [ ] - [tool.ruff.per-file-ignores] "webui.py" = ["E402"] # Module level import not at top of file + +[tool.ruff.flake8-bugbear] +# Allow default arguments like, e.g., `data: List[str] = fastapi.Query(None)`. +extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"] \ No newline at end of file -- 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 --- extensions-builtin/LDSR/ldsr_model_arch.py | 2 +- extensions-builtin/Lora/lora.py | 2 +- extensions-builtin/ScuNET/scripts/scunet_model.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 2 +- 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 +- pyproject.toml | 1 - scripts/prompts_from_file.py | 2 +- scripts/sd_upscale.py | 4 ++-- scripts/xyz_grid.py | 2 +- 28 files changed, 57 insertions(+), 62 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index a5fb8907..27e38549 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -88,7 +88,7 @@ class LDSR: x_t = None logs = None - for n in range(n_runs): + for _ in range(n_runs): if custom_shape is not None: x_t = torch.randn(1, custom_shape[1], custom_shape[2], custom_shape[3]).to(model.device) x_t = repeat(x_t, '1 c h w -> b c h w', b=custom_shape[0]) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 9795540f..7b56136f 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -418,7 +418,7 @@ def infotext_pasted(infotext, params): added = [] - for k, v in params.items(): + for k in params: if not k.startswith("AddNet Model "): continue diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index aa2fdb3a..1f5ea0d3 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -132,7 +132,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) model.load_state_dict(torch.load(filename), strict=True) model.eval() - for k, v in model.named_parameters(): + for _, v in model.named_parameters(): v.requires_grad = False model = model.to(device) diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 75f7bedc..de195d9b 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -848,7 +848,7 @@ class SwinIR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index d4c0b0da..15777af9 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -1001,7 +1001,7 @@ class Swin2SR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() 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) diff --git a/pyproject.toml b/pyproject.toml index 346a0cde..c88907be 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,7 +20,6 @@ ignore = [ "I001", # Import block is un-sorted or un-formatted "C901", # Function is too complex "C408", # Rewrite as a literal - "B007", # Loop control variable not used within loop body ] diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 149bc85f..27af5ff6 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -156,7 +156,7 @@ class Script(scripts.Script): images = [] all_prompts = [] infotexts = [] - for n, args in enumerate(jobs): + for args in jobs: state.job = f"{state.job_no + 1} out of {state.job_count}" copy_p = copy.copy(p) diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index d873a09c..0b1d3096 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -56,7 +56,7 @@ class Script(scripts.Script): work = [] - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: work.append(tiledata[2]) @@ -85,7 +85,7 @@ class Script(scripts.Script): work_results += processed.images image_index = 0 - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height)) image_index += 1 diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 332e0ecd..38a20381 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -704,7 +704,7 @@ class Script(scripts.Script): if not include_sub_grids: # Done with sub-grids, drop all related information: - for sg in range(z_count): + for _ in range(z_count): del processed.images[1] del processed.all_prompts[1] del processed.all_seeds[1] -- 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/generation_parameters_copypaste.py') 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 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 ++-- requirements.txt | 1 + requirements_versions.txt | 2 +- 4 files changed, 5 insertions(+), 4 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') 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"), { diff --git a/requirements.txt b/requirements.txt index 2423bfd2..302b3dab 100644 --- a/requirements.txt +++ b/requirements.txt @@ -29,3 +29,4 @@ torchsde safetensors psutil rich +tomesd diff --git a/requirements_versions.txt b/requirements_versions.txt index 0e03deed..17ae9484 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -26,4 +26,4 @@ torchsde==0.2.5 safetensors==0.3.1 httpcore<=0.15 fastapi==0.94.0 -tomesd>=0.1.2 \ No newline at end of file +tomesd==0.1.2 -- cgit v1.2.3