ti fixes

.gitignore

@@ -32,6 +32,8 @@ venv
 /models/**/*
 /interrogate/**/*
 /train/log/**/*
+/textual_inversion/**/*
+/detected_maps/**/*
 /tmp
 /log
 /cert

javascript/progressbar.js

@@ -77,7 +77,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd = null, o
         setTitle("")
         if (divProgress) parentProgressbar.removeChild(divProgress)
         if (parentGallery) parentGallery.removeChild(livePreview)
-        atEnd()
+        if (atEnd) atEnd()
     }
 
     var fun = function(id_task, id_live_preview){

javascript/textualInversion.js

@@ -5,6 +5,7 @@ function start_training_textual_inversion(){
     gradioApp().querySelector('#ti_error').innerHTML=''
     var id = randomId()
     const onProgress = (progress) => gradioApp().getElementById('ti_progress').innerHTML = progress.textinfo;
+    // requestProgress(id_task, progressbarContainer, gallery, atEnd = null, onProgress = null, once = false) {
     requestProgress(id, gradioApp().getElementById('ti_output'), gradioApp().getElementById('ti_gallery'), null, onProgress, false)
     var res = args_to_array(arguments)
     res[0] = id

modules/textual_inversion/textual_inversion.py

@@ -1,23 +1,19 @@
 import os
-from collections import namedtuple
-
-import torch
-import tqdm
 import html
 import csv
+from collections import namedtuple
+import torch
+import tqdm
 import safetensors.torch
-
+from rich import print # pylint: disable=redefined-builtin
 import numpy as np
 from PIL import Image, PngImagePlugin
 from torch.utils.tensorboard import SummaryWriter
-
 from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors
 import modules.textual_inversion.dataset
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
-
 from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay
 from modules.textual_inversion.logging import save_settings_to_file
-from rich import print # pylint: disable=redefined-builtin
 
 TextualInversionTemplate = namedtuple("TextualInversionTemplate", ["name", "path"])
 textual_inversion_templates = {}
@@ -26,7 +22,7 @@ textual_inversion_templates = {}
 def list_textual_inversion_templates():
     textual_inversion_templates.clear()
 
-    for root, dirs, fns in os.walk(shared.opts.embeddings_templates_dir):
+    for root, _dirs, fns in os.walk(shared.opts.embeddings_templates_dir):
         for fn in fns:
             path = os.path.join(root, fn)
 
@@ -198,7 +194,7 @@ class EmbeddingDatabase:
         if not os.path.isdir(embdir.path):
             return
 
-        for root, dirs, fns in os.walk(embdir.path, followlinks=True):
+        for root, _dirs, fns in os.walk(embdir.path, followlinks=True):
             for fn in fns:
                 try:
                     fullfn = os.path.join(root, fn)
@@ -214,7 +210,7 @@ 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 _path, embdir in self.embedding_dirs.items():
                 if embdir.has_changed():
                     need_reload = True
                     break
@@ -227,7 +223,7 @@ class EmbeddingDatabase:
         self.skipped_embeddings.clear()
         self.expected_shape = self.get_expected_shape()
 
-        for path, embdir in self.embedding_dirs.items():
+        for _path, embdir in self.embedding_dirs.items():
             self.load_from_dir(embdir)
             embdir.update()
 
@@ -270,13 +266,13 @@ def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'):
     # Remove illegal characters from name.
     name = "".join( x for x in name if (x.isalnum() or x in "._- "))
     fn = os.path.join(shared.opts.embeddings_dir, f"{name}.pt")
-    if not overwrite_old:
-        assert not os.path.exists(fn), f"file {fn} already exists"
-
-    embedding = Embedding(vec, name)
-    embedding.step = 0
-    embedding.save(fn)
-
+    if not overwrite_old and os.path.exists(fn):
+        print(f"Embedding already exists: {fn}")
+    else:
+        embedding = Embedding(vec, name)
+        embedding.step = 0
+        embedding.save(fn)
+        print(f'Created embedding: {fn} vectors {num_vectors_per_token} init {init_text}')
     return fn
 
 
@@ -288,7 +284,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
         return
     write_csv_header = False if os.path.exists(os.path.join(log_directory, filename)) else True
 
-    with open(os.path.join(log_directory, filename), "a+", newline='') as fout:
+    with open(os.path.join(log_directory, filename), "a+", newline='', encoding='utf-8') as fout:
         csv_writer = csv.DictWriter(fout, fieldnames=["step", "epoch", "epoch_step", *(values.keys())])
 
         if write_csv_header:
@@ -460,7 +456,7 @@ 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 _i in range((steps-initial_step) * gradient_step):
             if scheduler.finished:
                 break
             if shared.state.interrupted:
@@ -574,7 +570,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
                     if image is not None:
                         shared.state.assign_current_image(image)
 
-                        last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
+                        last_saved_image, _last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                         last_saved_image += f", prompt: {preview_text}"
 
                         if shared.opts.training_enable_tensorboard and shared.opts.training_tensorboard_save_images:
@@ -587,18 +583,17 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
                         info = PngImagePlugin.PngInfo()
                         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]
-                        except Exception as e:
+                        except Exception:
                             vectorSize = '?'
 
                         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)
@@ -606,7 +601,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
                         captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
                         embedding_yet_to_be_embedded = False
 
-                    last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
+                    last_saved_image, _last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                     last_saved_image += f", prompt: {preview_text}"
 
                 shared.state.job_no = embedding.step
@@ -624,7 +619,6 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True)
     except Exception as e:
         errors.display(e, 'embedding train')
-        pass
     finally:
         pbar.leave = False
         pbar.close()

modules/textual_inversion/ui.py

@@ -1,7 +1,5 @@
 import html
-
 import gradio as gr
-
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
 from modules import sd_hijack, shared
@@ -9,9 +7,7 @@ from modules import sd_hijack, shared
 
 def create_embedding(name, initialization_text, nvpt, overwrite_old):
     filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, overwrite_old, init_text=initialization_text)
-
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
-
     return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
 
 
@@ -42,4 +38,3 @@ Embedding saved to {html.escape(filename)}
     finally:
         if not apply_optimizations:
             sd_hijack.apply_optimizations()
-

modules/ui.py

@@ -1127,7 +1127,7 @@ def create_ui():
                         gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
 
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="train/log/embeddings", elem_id="train_log_directory")
 
                     with FormRow():
                         template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
@@ -1136,7 +1136,7 @@ def create_ui():
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
                     varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
-                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
+                    steps = gr.Number(label='Max steps', value=1000, precision=0, elem_id="train_steps")
 
                     with FormRow():
                         create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
@@ -1740,32 +1740,3 @@ def reload_javascript():
 
 if not hasattr(shared, 'GradioTemplateResponseOriginal'):
     shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
-
-
-def versions_html():
-    import torch
-    import launch
-
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    commit = launch.commit_hash()
-    short_commit = commit[0:8]
-
-    if shared.xformers_available:
-        import xformers
-        xformers_version = xformers.__version__
-    else:
-        xformers_version = "N/A"
-
-    return f"""
-python: <span title="{sys.version}">{python_version}</span>
- • 
-torch: {getattr(torch, '__long_version__',torch.__version__)}
- • 
-xformers: {xformers_version}
- • 
-gradio: {gr.__version__}
- • 
-commit: <a href="https://github.com/vladmandic/automatic/commit/{commit}">{short_commit}</a>
- • 
-checkpoint: <a id="sd_checkpoint_hash">N/A</a>
-"""

modules/ui_extra_networks_hypernets.py

@@ -1,6 +1,5 @@
 import json
 import os
-
 from modules import shared, ui_extra_networks
 
 
@@ -14,7 +13,6 @@ class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
     def list_items(self):
         for name, path in shared.hypernetworks.items():
             path, ext = os.path.splitext(path)
-
             yield {
                 "name": name,
                 "filename": path,

modules/ui_extra_networks_textual_inversion.py

@@ -25,12 +25,12 @@ class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
         for embedding in embeddings:
             path, _ext = os.path.splitext(embedding.filename)
             yield {
-                "name": embedding.name,
+                "name": os.path.splitext(embedding.name)[0],
                 "filename": embedding.filename,
                 "preview": self.find_preview(path),
                 "description": self.find_description(path),
                 "search_term": self.search_terms_from_path(embedding.filename),
-                "prompt": json.dumps(embedding.name),
+                "prompt": json.dumps(os.path.splitext(embedding.name)[0]),
                 "local_preview": f"{path}.preview.{shared.opts.samples_format}",
             }
 

setup.py

@@ -136,12 +136,18 @@ def update(folder):
     branch = git('branch', folder)
     if 'main' in branch:
         git('checkout main', folder)
+        branch = 'main'
     elif 'master' in branch:
         git('checkout master', folder)
+        branch = 'master'
     else:
         log.warning(f'Unknown branch for: {folder}')
-    git('pull --autostash --rebase', folder)
-    branch = git('branch', folder)
+        branch = None
+    if branch is None:
+        git('pull --autostash --rebase', folder)
+    else:
+        git(f'pull origin {branch} --autostash --rebase', folder)
+    # branch = git('branch', folder)
 
 
 # clone git repository