From 6435691bb11c5a35703720bfd2a875f24c066f86 Mon Sep 17 00:00:00 2001 From: Justin Maier Date: Sun, 9 Oct 2022 19:26:52 -0600 Subject: Add "Scale to" option to Extras --- modules/ui.py | 38 +++++++++++++++++++++++++------------- 1 file changed, 25 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 2231a8ed..4bb2892b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -101,7 +101,7 @@ def send_gradio_gallery_to_image(x): def save_files(js_data, images, do_make_zip, index): - import csv + import csv filenames = [] fullfns = [] @@ -551,7 +551,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - + with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) @@ -739,7 +739,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - + with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) @@ -903,7 +903,15 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Batch Process'): image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file") - upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) + with gr.Tabs(elem_id="extras_resize_mode"): + with gr.TabItem('Scale by'): + upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) + with gr.TabItem('Scale to'): + with gr.Group(): + with gr.Row(): + upscaling_resize_w = gr.Number(label="Width", value=512) + upscaling_resize_h = gr.Number(label="Height", value=512) + upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") @@ -934,6 +942,7 @@ def create_ui(wrap_gradio_gpu_call): fn=wrap_gradio_gpu_call(modules.extras.run_extras), _js="get_extras_tab_index", inputs=[ + dummy_component, dummy_component, extras_image, image_batch, @@ -941,6 +950,9 @@ def create_ui(wrap_gradio_gpu_call): codeformer_visibility, codeformer_weight, upscaling_resize, + upscaling_resize_w, + upscaling_resize_h, + upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, @@ -951,14 +963,14 @@ def create_ui(wrap_gradio_gpu_call): html_info, ] ) - + extras_send_to_img2img.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery_img2img", inputs=[result_images], outputs=[init_img], ) - + extras_send_to_inpaint.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery_img2img", @@ -1286,7 +1298,7 @@ Requested path was: {f} outputs=[], _js='function(){restart_reload()}' ) - + if column is not None: column.__exit__() @@ -1318,12 +1330,12 @@ Requested path was: {f} component_dict[k] = component settings_interface.gradio_ref = demo - + with gr.Tabs() as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid): interface.render() - + if os.path.exists(os.path.join(script_path, "notification.mp3")): audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) @@ -1456,10 +1468,10 @@ Requested path was: {f} if getattr(obj,'custom_script_source',None) is not None: key = 'customscript/' + obj.custom_script_source + '/' + key - + if getattr(obj, 'do_not_save_to_config', False): return - + saved_value = ui_settings.get(key, None) if saved_value is None: ui_settings[key] = getattr(obj, field) @@ -1483,10 +1495,10 @@ Requested path was: {f} if type(x) == gr.Textbox: apply_field(x, 'value') - + if type(x) == gr.Number: apply_field(x, 'value') - + visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") visit(extras_interface, loadsave, "extras") -- cgit v1.2.3 From 1f92336be768d235c18a82acb2195b7135101ae7 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Sun, 9 Oct 2022 23:58:18 -0500 Subject: refactored the deepbooru module to improve speed on running multiple interogations in a row. Added the option to generate deepbooru tags for textual inversion preproccessing. --- modules/deepbooru.py | 84 +++++++++++++++++++++++++-------- modules/textual_inversion/preprocess.py | 22 ++++++++- modules/ui.py | 52 ++++++++++++++------ 3 files changed, 122 insertions(+), 36 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 7e3c0618..cee4a3b4 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -1,21 +1,74 @@ import os.path from concurrent.futures import ProcessPoolExecutor -from multiprocessing import get_context +import multiprocessing -def _load_tf_and_return_tags(pil_image, threshold): +def get_deepbooru_tags(pil_image, threshold=0.5): + """ + This method is for running only one image at a time for simple use. Used to the img2img interrogate. + """ + from modules import shared # prevents circular reference + create_deepbooru_process(threshold) + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(pil_image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + release_process() + return ret + + +def deepbooru_process(queue, deepbooru_process_return, threshold): + model, tags = get_deepbooru_tags_model() + while True: # while process is running, keep monitoring queue for new image + pil_image = queue.get() + if pil_image == "QUIT": + break + else: + deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold) + + +def create_deepbooru_process(threshold=0.5): + """ + Creates deepbooru process. A queue is created to send images into the process. This enables multiple images + to be processed in a row without reloading the model or creating a new process. To return the data, a shared + dictionary is created to hold the tags created. To wait for tags to be returned, a value of -1 is assigned + to the dictionary and the method adding the image to the queue should wait for this value to be updated with + the tags. + """ + from modules import shared # prevents circular reference + shared.deepbooru_process_manager = multiprocessing.Manager() + shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue() + shared.deepbooru_process_return = shared.deepbooru_process_manager.dict() + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold)) + shared.deepbooru_process.start() + + +def release_process(): + """ + Stops the deepbooru process to return used memory + """ + from modules import shared # prevents circular reference + shared.deepbooru_process_queue.put("QUIT") + shared.deepbooru_process.join() + shared.deepbooru_process_queue = None + shared.deepbooru_process = None + shared.deepbooru_process_return = None + shared.deepbooru_process_manager = None + +def get_deepbooru_tags_model(): import deepdanbooru as dd import tensorflow as tf import numpy as np - this_folder = os.path.dirname(__file__) model_path = os.path.abspath(os.path.join(this_folder, '..', 'models', 'deepbooru')) if not os.path.exists(os.path.join(model_path, 'project.json')): # there is no point importing these every time import zipfile from basicsr.utils.download_util import load_file_from_url - load_file_from_url(r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip", - model_path) + load_file_from_url( + r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip", + model_path) with zipfile.ZipFile(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"), "r") as zip_ref: zip_ref.extractall(model_path) os.remove(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip")) @@ -24,7 +77,13 @@ def _load_tf_and_return_tags(pil_image, threshold): model = dd.project.load_model_from_project( model_path, compile_model=True ) + return model, tags + +def get_deepbooru_tags_from_model(model, tags, pil_image, threshold=0.5): + import deepdanbooru as dd + import tensorflow as tf + import numpy as np width = model.input_shape[2] height = model.input_shape[1] image = np.array(pil_image) @@ -57,17 +116,4 @@ def _load_tf_and_return_tags(pil_image, threshold): print('\n'.join(sorted(result_tags_print, reverse=True))) - return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') - - -def subprocess_init_no_cuda(): - import os - os.environ["CUDA_VISIBLE_DEVICES"] = "-1" - - -def get_deepbooru_tags(pil_image, threshold=0.5): - context = get_context('spawn') - with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor: - f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, ) - ret = f.result() # will rethrow any exceptions - return ret \ No newline at end of file + return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') \ No newline at end of file diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index f1c002a2..9f63c9a4 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -3,11 +3,14 @@ from PIL import Image, ImageOps import platform import sys import tqdm +import time from modules import shared, images +from modules.shared import opts, cmd_opts +if cmd_opts.deepdanbooru: + import modules.deepbooru as deepbooru - -def preprocess(process_src, process_dst, process_flip, process_split, process_caption): +def preprocess(process_src, process_dst, process_flip, process_split, process_caption, process_caption_deepbooru=False): size = 512 src = os.path.abspath(process_src) dst = os.path.abspath(process_dst) @@ -24,10 +27,21 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca if process_caption: shared.interrogator.load() + if process_caption_deepbooru: + deepbooru.create_deepbooru_process() + def save_pic_with_caption(image, index): if process_caption: caption = "-" + shared.interrogator.generate_caption(image) caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") + elif process_caption_deepbooru: + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + caption = "-" + shared.deepbooru_process_return["value"] + caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") + shared.deepbooru_process_return["value"] = -1 else: caption = filename caption = os.path.splitext(caption)[0] @@ -79,6 +93,10 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca if process_caption: shared.interrogator.send_blip_to_ram() + if process_caption_deepbooru: + deepbooru.release_process() + + def sanitize_caption(base_path, original_caption, suffix): operating_system = platform.system().lower() if (operating_system == "windows"): diff --git a/modules/ui.py b/modules/ui.py index 2231a8ed..179e3a83 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1034,6 +1034,9 @@ def create_ui(wrap_gradio_gpu_call): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images into two') process_caption = gr.Checkbox(label='Use BLIP caption as filename') + if cmd_opts.deepdanbooru: + process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename') + with gr.Row(): with gr.Column(scale=3): @@ -1086,21 +1089,40 @@ def create_ui(wrap_gradio_gpu_call): ] ) - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) + if cmd_opts.deepdanbooru: + # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + process_caption_deepbooru, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) + else: + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) train_embedding.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), -- cgit v1.2.3 From 8ec069e64df48f8f202f8b93a08e91b69448eb39 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Mon, 10 Oct 2022 03:23:24 -0500 Subject: removed duplicate run_preprocess.click by creating run_preprocess_inputs list and appending deepbooru variable to input list if in scope --- modules/ui.py | 49 +++++++++++++++++-------------------------------- 1 file changed, 17 insertions(+), 32 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 179e3a83..22ca74c2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1089,40 +1089,25 @@ def create_ui(wrap_gradio_gpu_call): ] ) + run_preprocess_inputs = [ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ] if cmd_opts.deepdanbooru: # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - process_caption_deepbooru, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) - else: - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) + run_preprocess_inputs.append(process_caption_deepbooru) + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=run_preprocess_inputs, + outputs=[ + ti_output, + ti_outcome, + ], + ) train_embedding.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), -- cgit v1.2.3 From 2f94331df2cb1181439adecc28cfd758049f6501 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Mon, 10 Oct 2022 03:34:00 -0500 Subject: removed change in last commit, simplified to adding the visible argument to process_caption_deepbooru and it set to False if deepdanbooru argument is not set --- modules/ui.py | 22 ++++++++++------------ 1 file changed, 10 insertions(+), 12 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 22ca74c2..f8adafb3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1036,7 +1036,8 @@ def create_ui(wrap_gradio_gpu_call): process_caption = gr.Checkbox(label='Use BLIP caption as filename') if cmd_opts.deepdanbooru: process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename') - + else: + process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False) with gr.Row(): with gr.Column(scale=3): @@ -1089,20 +1090,17 @@ def create_ui(wrap_gradio_gpu_call): ] ) - run_preprocess_inputs = [ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ] - if cmd_opts.deepdanbooru: - # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled - run_preprocess_inputs.append(process_caption_deepbooru) run_preprocess.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", - inputs=run_preprocess_inputs, + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + process_caption_deepbooru + ], outputs=[ ti_output, ti_outcome, -- cgit v1.2.3 From 1d64976dbc5a0f3124567b91fadd5014a9d93c5f Mon Sep 17 00:00:00 2001 From: Justin Maier Date: Mon, 10 Oct 2022 12:04:21 -0600 Subject: Simplify crop logic --- modules/extras.py | 14 +++----------- modules/ui.py | 4 ++-- 2 files changed, 5 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/extras.py b/modules/extras.py index 83ca7049..b24d7de3 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -73,16 +73,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, crop_info = " (crop)" if upscaling_crop else "" info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n" - def crop_upscaled_center(image, resize_w, resize_h): - left = int(math.ceil((image.width - resize_w) / 2)) - right = image.width - int(math.floor((image.width - resize_w) / 2)) - top = int(math.ceil((image.height - resize_h) / 2)) - bottom = image.height - int(math.floor((image.height - resize_h) / 2)) - - image = image.crop((left, top, right, bottom)) - return image - - if upscaling_resize != 1.0: def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop): small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10)) @@ -94,7 +84,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, upscaler = shared.sd_upscalers[scaler_index] c = upscaler.scaler.upscale(image, resize, upscaler.data_path) if mode == 1 and crop: - c = crop_upscaled_center(c, resize_w, resize_h) + cropped = Image.new("RGB", (resize_w, resize_h)) + cropped.paste(c, box=(resize_w // 2 - c.width // 2, resize_h // 2 - c.height // 2)) + c = cropped cached_images[key] = c return c diff --git a/modules/ui.py b/modules/ui.py index 4bb2892b..1aabe18d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -909,8 +909,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Scale to'): with gr.Group(): with gr.Row(): - upscaling_resize_w = gr.Number(label="Width", value=512) - upscaling_resize_h = gr.Number(label="Height", value=512) + upscaling_resize_w = gr.Number(label="Width", value=512, precision=0) + upscaling_resize_h = gr.Number(label="Height", value=512, precision=0) upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): -- cgit v1.2.3 From 2536ecbb1790da2af0d61b6a26f38732cba665cd Mon Sep 17 00:00:00 2001 From: Fampai <> Date: Mon, 10 Oct 2022 17:10:29 -0400 Subject: Refactored learning rate code --- modules/textual_inversion/textual_inversion.py | 51 ++++++++++++++++++++++++-- modules/ui.py | 2 +- 2 files changed, 48 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 5965c5a0..c64a4598 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -189,8 +189,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini embedding = hijack.embedding_db.word_embeddings[embedding_name] embedding.vec.requires_grad = True - optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) - losses = torch.zeros((32,)) last_saved_file = "" @@ -203,12 +201,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]) epoch_len = (tr_img_len * num_repeats) + tr_img_len + scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(scheduleIter) + print(f'Training at rate of {learn_rate} until step {end_step}') + + optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) + pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) for i, (x, text) in pbar: embedding.step = i + ititial_step - if embedding.step > steps: - break + if embedding.step > end_step: + try: + (learn_rate, end_step) = next(scheduleIter) + except: + break + tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') + for pg in optimizer.param_groups: + pg['lr'] = learn_rate if shared.state.interrupted: break @@ -277,3 +287,36 @@ Last saved image: {html.escape(last_saved_image)}
return embedding, filename +class LearnSchedule: + def __init__(self, learn_rate, max_steps, cur_step=0): + pairs = learn_rate.split(',') + self.rates = [] + self.it = 0 + self.maxit = 0 + for i, pair in enumerate(pairs): + tmp = pair.split(':') + if len(tmp) == 2: + step = int(tmp[1]) + if step > cur_step: + self.rates.append((float(tmp[0]), min(step, max_steps))) + self.maxit += 1 + if step > max_steps: + return + elif step == -1: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + else: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + + def __iter__(self): + return self + + def __next__(self): + if self.it < self.maxit: + self.it += 1 + return self.rates[self.it - 1] + else: + raise StopIteration diff --git a/modules/ui.py b/modules/ui.py index 8c06ad7c..c9e8355b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1047,7 +1047,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) - learn_rate = gr.Number(label='Learning rate', value=5.0e-03) + learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03") dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) -- cgit v1.2.3 From 1add3cff84b7e2436d69b1e97ae689281e4a7c33 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Mon, 10 Oct 2022 19:57:43 -0500 Subject: Refresh list of models/ckpts upon hitting restart gradio in the settings pane --- modules/ui.py | 4 ++++ 1 file changed, 4 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e8039d76..06ff118f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,6 +39,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui +from modules.sd_models import list_models # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1290,6 +1291,9 @@ Requested path was: {f} shared.state.interrupt() settings_interface.gradio_ref.do_restart = True + # refresh models so that new models/.ckpt's show up on reload + list_models() + restart_gradio.click( fn=request_restart, inputs=[], -- cgit v1.2.3 From d01a2d01560b31937df1f3433d210c18f97d32fa Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 11 Oct 2022 08:03:31 -0500 Subject: move list refresh to webui.py and add stdout indicating it's doing so --- modules/ui.py | 3 --- webui.py | 2 ++ 2 files changed, 2 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 06ff118f..ae9317a3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,7 +39,6 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui -from modules.sd_models import list_models # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1291,8 +1290,6 @@ Requested path was: {f} shared.state.interrupt() settings_interface.gradio_ref.do_restart = True - # refresh models so that new models/.ckpt's show up on reload - list_models() restart_gradio.click( fn=request_restart, diff --git a/webui.py b/webui.py index 270584f7..94098c4c 100644 --- a/webui.py +++ b/webui.py @@ -124,6 +124,8 @@ def webui(): modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) print('Reloading modules: modules.ui') importlib.reload(modules.ui) + print('Refreshing Model List') + modules.sd_models.list_models() print('Restarting Gradio') -- cgit v1.2.3 From d682444ecc99319fbd2b142a12727501e2884ba7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 18:04:47 +0300 Subject: add option to select hypernetwork modules when creating --- modules/hypernetworks/hypernetwork.py | 4 ++-- modules/hypernetworks/ui.py | 4 ++-- modules/ui.py | 2 ++ 3 files changed, 6 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index aa701bda..b081f14e 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -42,7 +42,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None): + def __init__(self, name=None, enable_sizes=None): self.filename = None self.name = name self.layers = {} @@ -50,7 +50,7 @@ class Hypernetwork: self.sd_checkpoint = None self.sd_checkpoint_name = None - for size in [320, 640, 768, 1280]: + for size in enable_sizes or [320, 640, 768, 1280]: self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) def weights(self): diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index e7540f41..cdddcce1 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -9,11 +9,11 @@ from modules import sd_hijack, shared from modules.hypernetworks import hypernetwork -def create_hypernetwork(name): +def create_hypernetwork(name, enable_sizes): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" - hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name) + hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes]) hypernet.save(fn) shared.reload_hypernetworks() diff --git a/modules/ui.py b/modules/ui.py index f2d16b12..14b87b92 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1037,6 +1037,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

Create a new hypernetwork

") new_hypernetwork_name = gr.Textbox(label="Name") + new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) with gr.Row(): with gr.Column(scale=3): @@ -1114,6 +1115,7 @@ def create_ui(wrap_gradio_gpu_call): fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ new_hypernetwork_name, + new_hypernetwork_sizes, ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From d6fcc6b87bc00fcdecea276fe5b7c7945f7a8b14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 22:03:05 +0300 Subject: apply lr schedule to hypernets --- modules/hypernetworks/hypernetwork.py | 19 ++++++++--- modules/textual_inversion/learn_schedule.py | 34 ++++++++++++++++++++ modules/textual_inversion/textual_inversion.py | 44 +++----------------------- modules/ui.py | 2 +- 4 files changed, 54 insertions(+), 45 deletions(-) create mode 100644 modules/textual_inversion/learn_schedule.py (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 5608e799..470659df 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -14,6 +14,7 @@ import torch from torch import einsum from einops import rearrange, repeat import modules.textual_inversion.dataset +from modules.textual_inversion.learn_schedule import LearnSchedule class HypernetworkModule(torch.nn.Module): @@ -202,8 +203,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, for weight in weights: weight.requires_grad = True - optimizer = torch.optim.AdamW(weights, lr=learn_rate) - losses = torch.zeros((32,)) last_saved_file = "" @@ -213,12 +212,24 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if ititial_step > steps: return hypernetwork, filename + schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(schedules) + print(f'Training at rate of {learn_rate} until step {end_step}') + + optimizer = torch.optim.AdamW(weights, lr=learn_rate) + pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) for i, (x, text, cond) in pbar: hypernetwork.step = i + ititial_step - if hypernetwork.step > steps: - break + if hypernetwork.step > end_step: + try: + (learn_rate, end_step) = next(schedules) + except Exception: + break + tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') + for pg in optimizer.param_groups: + pg['lr'] = learn_rate if shared.state.interrupted: break diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py new file mode 100644 index 00000000..db720271 --- /dev/null +++ b/modules/textual_inversion/learn_schedule.py @@ -0,0 +1,34 @@ + +class LearnSchedule: + def __init__(self, learn_rate, max_steps, cur_step=0): + pairs = learn_rate.split(',') + self.rates = [] + self.it = 0 + self.maxit = 0 + for i, pair in enumerate(pairs): + tmp = pair.split(':') + if len(tmp) == 2: + step = int(tmp[1]) + if step > cur_step: + self.rates.append((float(tmp[0]), min(step, max_steps))) + self.maxit += 1 + if step > max_steps: + return + elif step == -1: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + else: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + + def __iter__(self): + return self + + def __next__(self): + if self.it < self.maxit: + self.it += 1 + return self.rates[self.it - 1] + else: + raise StopIteration diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 47a27faf..7717837d 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -10,6 +10,7 @@ import datetime from modules import shared, devices, sd_hijack, processing, sd_models import modules.textual_inversion.dataset +from modules.textual_inversion.learn_schedule import LearnSchedule class Embedding: @@ -198,11 +199,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if ititial_step > steps: return embedding, filename - tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]) - epoch_len = (tr_img_len * num_repeats) + tr_img_len - - scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step)) - (learn_rate, end_step) = next(scheduleIter) + schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(schedules) print(f'Training at rate of {learn_rate} until step {end_step}') optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) @@ -213,7 +211,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > end_step: try: - (learn_rate, end_step) = next(scheduleIter) + (learn_rate, end_step) = next(schedules) except: break tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') @@ -288,37 +286,3 @@ Last saved image: {html.escape(last_saved_image)}
embedding.save(filename) return embedding, filename - -class LearnSchedule: - def __init__(self, learn_rate, max_steps, cur_step=0): - pairs = learn_rate.split(',') - self.rates = [] - self.it = 0 - self.maxit = 0 - for i, pair in enumerate(pairs): - tmp = pair.split(':') - if len(tmp) == 2: - step = int(tmp[1]) - if step > cur_step: - self.rates.append((float(tmp[0]), min(step, max_steps))) - self.maxit += 1 - if step > max_steps: - return - elif step == -1: - self.rates.append((float(tmp[0]), max_steps)) - self.maxit += 1 - return - else: - self.rates.append((float(tmp[0]), max_steps)) - self.maxit += 1 - return - - def __iter__(self): - return self - - def __next__(self): - if self.it < self.maxit: - self.it += 1 - return self.rates[self.it - 1] - else: - raise StopIteration diff --git a/modules/ui.py b/modules/ui.py index 2b688e32..1204eef7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1070,7 +1070,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) - learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03") + learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) -- cgit v1.2.3 From f53f703aebc801c4204182d52bb1e0bef9808e1f Mon Sep 17 00:00:00 2001 From: JC_Array Date: Tue, 11 Oct 2022 18:12:12 -0500 Subject: resolved conflicts, moved settings under interrogate section, settings only show if deepbooru flag is enabled --- modules/deepbooru.py | 2 +- modules/shared.py | 19 +++++++++---------- modules/textual_inversion/preprocess.py | 2 +- modules/ui.py | 2 +- 4 files changed, 12 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 89dcac3c..29529949 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -8,7 +8,7 @@ def get_deepbooru_tags(pil_image): This method is for running only one image at a time for simple use. Used to the img2img interrogate. """ from modules import shared # prevents circular reference - create_deepbooru_process(shared.opts.deepbooru_threshold, shared.opts.deepbooru_sort_alpha) + create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha) shared.deepbooru_process_return["value"] = -1 shared.deepbooru_process_queue.put(pil_image) while shared.deepbooru_process_return["value"] == -1: diff --git a/modules/shared.py b/modules/shared.py index 817203f8..5456c477 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -248,15 +248,20 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}), })) -options_templates.update(options_section(('interrogate', "Interrogate Options"), { +interrogate_option_dictionary = { "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"), "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), -})) + "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)") +} + +if cmd_opts.deepdanbooru: + interrogate_option_dictionary["interrogate_deepbooru_score_threshold"] = OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}) + interrogate_option_dictionary["deepbooru_sort_alpha"] = OptionInfo(True, "Interrogate: deepbooru sort alphabetically", gr.Checkbox) + +options_templates.update(options_section(('interrogate', "Interrogate Options"), interrogate_option_dictionary)) options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), @@ -282,12 +287,6 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) -if cmd_opts.deepdanbooru: - options_templates.update(options_section(('deepbooru-params', "DeepBooru parameters"), { - "deepbooru_sort_alpha": OptionInfo(True, "Sort Alphabetical", gr.Checkbox), - 'deepbooru_threshold': OptionInfo(0.5, "Threshold", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - })) - class Options: data = None diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index a96388d6..113cecf1 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -29,7 +29,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ shared.interrogator.load() if process_caption_deepbooru: - deepbooru.create_deepbooru_process(opts.deepbooru_threshold, opts.deepbooru_sort_alpha) + deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha) def save_pic_with_caption(image, index): if process_caption: diff --git a/modules/ui.py b/modules/ui.py index 2891fc8c..fa45edca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -317,7 +317,7 @@ def interrogate(image): def interrogate_deepbooru(image): - prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold) + prompt = get_deepbooru_tags(image) return gr_show(True) if prompt is None else prompt -- cgit v1.2.3 From fec2221eeaafb50afd26ba3e109bf6f928011e69 Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Tue, 11 Oct 2022 19:29:38 -0700 Subject: Truncate error text to fix service lockup / stall What: * Update wrap_gradio_call to add a limit to the maximum amount of text output Why: * wrap_gradio_call currently prints out a list of the arguments provided to the failing function. * if that function is save_image, this causes the entire image to be printed to stderr * If the image is large, this can cause the service to lock up while attempting to print all the text * It is easy to generate large images using the x/y plot script * it is easy to encounter image save exceptions, including if the output directory does not exist / cannot be written to, or if the file is too big * The huge amount of log spam is confusing and not particularly helpful --- modules/ui.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 1204eef7..33a49d3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -181,8 +181,15 @@ def wrap_gradio_call(func, extra_outputs=None): try: res = list(func(*args, **kwargs)) except Exception as e: + # When printing out our debug argument list, do not print out more than a MB of text + max_debug_str_len = 131072 # (1024*1024)/8 + print("Error completing request", file=sys.stderr) - print("Arguments:", args, kwargs, file=sys.stderr) + argStr = f"Arguments: {str(args)} {str(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) + print(traceback.format_exc(), file=sys.stderr) shared.state.job = "" -- cgit v1.2.3 From 57e03cdd244eee4e33ccab7554b3594563a3d0cd Mon Sep 17 00:00:00 2001 From: brkirch Date: Wed, 12 Oct 2022 00:54:24 -0400 Subject: Ensure the directory exists before saving to it The directory for the images saved with the Save button may still not exist, so it needs to be created prior to opening the log.csv file. --- modules/ui.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 00bf09ae..cd67b84b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -131,6 +131,8 @@ def save_files(js_data, images, do_make_zip, index): images = [images[index]] start_index = index + os.makedirs(opts.outdir_save, exist_ok=True) + with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file: at_start = file.tell() == 0 writer = csv.writer(file) -- cgit v1.2.3 From ee015a1af66a94a75c914659fa0d321e702a0a87 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 12 Oct 2022 11:05:57 +0300 Subject: change textual inversion tab to train remake train interface to use tabs --- modules/hypernetworks/hypernetwork.py | 2 +- modules/ui.py | 22 +++++++++------------- 2 files changed, 10 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 8f2192e2..8314450a 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -175,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): - assert hypernetwork_name, 'embedding not selected' + assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) shared.loaded_hypernetwork = Hypernetwork() diff --git a/modules/ui.py b/modules/ui.py index 4bfdd275..86a2da6c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1035,14 +1035,14 @@ def create_ui(wrap_gradio_gpu_call): sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() - with gr.Blocks() as textual_inversion_interface: + with gr.Blocks() as train_interface: with gr.Row().style(equal_height=False): - with gr.Column(): - with gr.Group(): - gr.HTML(value="

See wiki for detailed explanation.

") + gr.HTML(value="

See wiki for detailed explanation.

") - gr.HTML(value="

Create a new embedding

") + with gr.Row().style(equal_height=False): + with gr.Tabs(elem_id="train_tabs"): + with gr.Tab(label="Create embedding"): new_embedding_name = gr.Textbox(label="Name") initialization_text = gr.Textbox(label="Initialization text", value="*") nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) @@ -1054,9 +1054,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') - with gr.Group(): - gr.HTML(value="

Create a new hypernetwork

") - + with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) @@ -1067,9 +1065,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary') - with gr.Group(): - gr.HTML(value="

Preprocess images

") - + with gr.Tab(label="Preprocess images"): process_src = gr.Textbox(label='Source directory') process_dst = gr.Textbox(label='Destination directory') process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) @@ -1091,7 +1087,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): run_preprocess = gr.Button(value="Preprocess", variant='primary') - with gr.Group(): + with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) @@ -1388,7 +1384,7 @@ Requested path was: {f} (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), - (textual_inversion_interface, "Textual inversion", "ti"), + (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), ] -- cgit v1.2.3