Merge branch 'dev' into ipadapter-end

CHANGELOG.md

@@ -1,6 +1,6 @@
 # Change Log for SD.Next
 
-## Update for 2024-02-10
+## Update for 2024-02-12
 
 - **improvements**:
   - **IP Adapter** major refactor  
@@ -9,7 +9,7 @@
       *note*: you cannot mix & match ip adapters that use different *CLiP* models, for example `Base` and `Base ViT-G`  
     - unified interface in txt2img, img2img and control  
     - enhanced xyz grid support  
-  - **FaceID** now works with multiple input images  
+  - **FaceID** now also works with multiple input images!  
   - **CFG End** new param to control image generation guidance, thanks @AI-Casanova  
     sometimes you want strong control over composition, but you want it to stop at some point  
     for example, when used with ip-adapters or controlnet, high cfg scale can overpower the guided image  
@@ -55,6 +55,11 @@
   - lazy loading of image may prevent metadata from being loaded on time  
   - allow startup without valid models folder  
   - fix interrogate api endpoint  
+  - control fix resize causing runtime errors  
+  - control fix processor override image after processor change  
+  - fix vae dtype mismatch, thanks @Disty0  
+  - fix controlnet inpaint mask  
+  - bind controlnet extension to last known working commit, thanks @Aptronymist  
   - handle extensions that install conflicting versions of packages  
     `onnxruntime`, `opencv2-python`  
 

TODO.md

@@ -4,12 +4,12 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 
 ## Candidates for next release
 
-- diffusers public callbacks  
 - control second pass: <https://github.com/vladmandic/automatic/issues/2783>  
+- onediff: <https://github.com/siliconflow/onediff>
+- diffusers public callbacks  
 - image2video: pia and vgen pipelines  
 - video2video
 - control api  
 - masking api  
 - preprocess api  
 - bind panZoom to control input
-- onediff: <https://github.com/siliconflow/onediff>

installer.py

@@ -47,7 +47,7 @@ args = Dot({
 })
 git_commit = "unknown"
 submodules_commit = {
-    # 'sd-webui-controlnet': 'ecd33eb',
+    'sd-webui-controlnet': 'ecd33eb',
     # 'stable-diffusion-webui-images-browser': '27fe4a7',
 }
 
@@ -456,12 +456,6 @@ def check_torch():
         xformers_package = os.environ.get('XFORMERS_PACKAGE', 'none')
         if rocm_ver is not None:
             install(os.environ.get('ONNXRUNTIME_PACKAGE', get_onnxruntime_source_for_rocm(arr)), "onnxruntime-training built with ROCm", ignore=True)
-            try:
-                import onnxruntime
-                if "ROCMExecutionProvider" not in onnxruntime.get_available_providers():
-                    log.warning('Failed to automatically install onxnruntime package for ROCm. Please manually install it if you need.')
-            except Exception:
-                pass
     elif allow_ipex and (args.use_ipex or shutil.which('sycl-ls') is not None or shutil.which('sycl-ls.exe') is not None or os.environ.get('ONEAPI_ROOT') is not None or os.path.exists('/opt/intel/oneapi') or os.path.exists("C:/Program Files (x86)/Intel/oneAPI") or os.path.exists("C:/oneAPI")):
         args.use_ipex = True # pylint: disable=attribute-defined-outside-init
         log.info('Intel OneAPI Toolkit detected')
@@ -864,7 +858,10 @@ def get_onnxruntime_source_for_rocm(rocm_ver):
     if rocm_ver is None:
         command = subprocess.run('hipconfig --version', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
         rocm_ver = command.stdout.decode(encoding="utf8", errors="ignore").split('.')
-    return f"https://download.onnxruntime.ai/onnxruntime_training-{ort_version}%2Brocm{rocm_ver[0]}{rocm_ver[1]}-cp{cp_str}-cp{cp_str}-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"
+    if "linux" in sys.platform:
+        return f"https://download.onnxruntime.ai/onnxruntime_training-{ort_version}%2Brocm{rocm_ver[0]}{rocm_ver[1]}-cp{cp_str}-cp{cp_str}-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"
+    else:
+        return 'onnxruntime-gpu'
 
 
 # check version of the main repo and optionally upgrade it

modules/control/processors.py

@@ -126,7 +126,7 @@ class Processor():
     def __init__(self, processor_id: str = None, resize = True):
         self.model = None
         self.processor_id = None
-        # self.override = None
+        self.override = None
         self.resize = resize
         self.reset()
         self.config(processor_id)
@@ -138,7 +138,7 @@ class Processor():
             debug(f'Control Processor unloaded: id="{self.processor_id}"')
         self.model = None
         self.processor_id = processor_id
-        self.override = None
+        # self.override = None
         devices.torch_gc()
         self.load_config = { 'cache_dir': cache_dir }
 
@@ -215,8 +215,8 @@ class Processor():
             if resize_mode != 0 and resize_name != 'None':
                 if scale_tab == 1:
                     width_before, height_before = int(image_input.width * scale_by), int(image_input.height * scale_by)
-                debug(f'Control resize: op=before image={image_input} width={width_before} height={height_before} mode={resize_mode} name={resize_name}')
-                image_input = images.resize_image(resize_mode, image_input, width_before, height_before, resize_name)
+                    debug(f'Control resize: op=before image={image_input} width={width_before} height={height_before} mode={resize_mode} name={resize_name}')
+                    image_input = images.resize_image(resize_mode, image_input, width_before, height_before, resize_name)
         image_process = image_input
         if image_input is None:
             # log.error('Control Processor: no input')

modules/generation_parameters_copypaste.py

@@ -6,7 +6,7 @@ import json
 from PIL import Image
 import gradio as gr
 from modules.paths import data_path
-from modules import shared, ui_tempdir, script_callbacks, images
+from modules import shared, gr_tempdir, script_callbacks, images
 
 
 re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)'
@@ -58,7 +58,7 @@ def image_from_url_text(filedata):
         filedata = filedata[0]
     if type(filedata) == dict and filedata.get("is_file", False):
         filename = filedata["name"]
-        is_in_right_dir = ui_tempdir.check_tmp_file(shared.demo, filename)
+        is_in_right_dir = gr_tempdir.check_tmp_file(shared.demo, filename)
         if is_in_right_dir:
             filename = filename.rsplit('?', 1)[0]
             if not os.path.exists(filename):

modules/gr_hijack.py

@@ -1,6 +1,13 @@
 from PIL import Image
 import gradio as gr
 import gradio.processing_utils
+from modules import scripts, patches, gr_tempdir
+
+
+original_IOComponent_init = None
+original_Block_get_config = None
+original_BlockContext_init = None
+original_Blocks_get_config_file = None
 
 
 def gr_image_preprocess(self, x):
@@ -25,5 +32,62 @@ def gr_image_preprocess(self, x):
     return self._format_image(im) # pylint: disable=protected-access
 
 
+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 = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])]
+    if getattr(comp, 'multiselect', False):
+        comp.elem_classes.append('multiselect')
+
+
+def IOComponent_init(self, *args, **kwargs):
+    self.webui_tooltip = kwargs.pop('tooltip', None)
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.before_component(self, **kwargs)
+    scripts.script_callbacks.before_component_callback(self, **kwargs)
+    res = original_IOComponent_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
+    add_classes_to_gradio_component(self)
+    scripts.script_callbacks.after_component_callback(self, **kwargs)
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.after_component(self, **kwargs)
+    return res
+
+
+def Block_get_config(self):
+    config = original_Block_get_config(self)
+    webui_tooltip = getattr(self, 'webui_tooltip', None)
+    if webui_tooltip:
+        config["webui_tooltip"] = webui_tooltip
+    config.pop('example_inputs', None)
+    return config
+
+
+def BlockContext_init(self, *args, **kwargs):
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.before_component(self, **kwargs)
+    scripts.script_callbacks.before_component_callback(self, **kwargs)
+    res = original_BlockContext_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
+    add_classes_to_gradio_component(self)
+    scripts.script_callbacks.after_component_callback(self, **kwargs)
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.after_component(self, **kwargs)
+    return res
+
+
+def Blocks_get_config_file(self, *args, **kwargs):
+    config = original_Blocks_get_config_file(self, *args, **kwargs)
+    for comp_config in config["components"]:
+        if "example_inputs" in comp_config:
+            comp_config["example_inputs"] = {"serialized": []}
+    return config
+
+
 def init():
+    global original_IOComponent_init, original_Block_get_config, original_BlockContext_init, original_Blocks_get_config_file # pylint: disable=global-statement
     gr.components.Image.preprocess =  gr_image_preprocess
+    gr.components.IOComponent.pil_to_temp_file =  gr_tempdir.pil_to_temp_file
+    original_IOComponent_init = patches.patch(__name__, obj=gr.components.IOComponent, field="__init__", replacement=IOComponent_init)
+    original_Block_get_config = patches.patch(__name__, obj=gr.blocks.Block, field="get_config", replacement=Block_get_config)
+    original_BlockContext_init = patches.patch(__name__, obj=gr.blocks.BlockContext, field="__init__", replacement=BlockContext_init)
+    original_Blocks_get_config_file = patches.patch(__name__, obj=gr.blocks.Blocks, field="get_config_file", replacement=Blocks_get_config_file)

modules/gr_tempdir.py

@@ -2,7 +2,6 @@ import os
 import tempfile
 from collections import namedtuple
 from pathlib import Path
-import gradio as gr
 from PIL import Image, PngImagePlugin
 from modules import shared, errors, paths
 
@@ -79,7 +78,6 @@ def pil_to_temp_file(self, img: Image, dir: str, format="png") -> str: # pylint:
 
 
 # override save to file function so that it also writes PNG info
-gr.components.IOComponent.pil_to_temp_file = pil_to_temp_file # gradio >=3.32.0
 
 def on_tmpdir_changed():
     if shared.opts.temp_dir == "":

modules/masking.py

@@ -12,6 +12,10 @@ from modules import shared, errors, devices, ui_components, ui_symbols, paths
 from modules.memstats import memory_stats
 
 
+debug = shared.log.trace if os.environ.get('SD_MASK_DEBUG', None) is not None else lambda *args, **kwargs: None
+debug('Trace: MASK')
+
+
 def get_crop_region(mask, pad=0):
     """finds a rectangular region that contains all masked ares in an image. Returns (x1, y1, x2, y2) coordinates of the rectangle.
     For example, if a user has painted the top-right part of a 512x512 image", the result may be (256, 0, 512, 256)"""
@@ -36,12 +40,22 @@ def get_crop_region(mask, pad=0):
         if not (mask[i] == 0).all():
             break
         crop_bottom += 1
-    return (
-        int(max(crop_left-pad, 0)),
-        int(max(crop_top-pad, 0)),
-        int(min(w - crop_right + pad, w)),
-        int(min(h - crop_bottom + pad, h))
+    x1 = max(crop_left - pad, 0)
+    y1 = max(crop_top - pad, 0)
+    x2 = max(w - crop_right + pad, 0)
+    y2 = max(h - crop_bottom + pad, 0)
+    if x2 < x1:
+        x1, x2 = x2, x1
+    if y2 < y1:
+        y1, y2 = y2, y1
+    crop_region = (
+        int(min(x1, w)),
+        int(min(y1, h)),
+        int(min(x2, w)),
+        int(min(y2, h)),
     )
+    debug(f'Mask crop: mask={mask.shape} region={crop_region} pad={pad}')
+    return crop_region
 
 
 def expand_crop_region(crop_region, processing_width, processing_height, image_width, image_height):
@@ -79,8 +93,14 @@ def expand_crop_region(crop_region, processing_width, processing_height, image_w
             x1 -= x1
         if x2 >= image_width:
             x2 = image_width
-
-    return x1, y1, x2, y2
+    crop_expand = (
+        int(x1),
+        int(y1),
+        int(x2),
+        int(y2),
+    )
+    debug(f'Mask expand: region={crop_expand} processing={processing_width}x{processing_height} image={image_width}x{image_height}')
+    return crop_expand
 
 
 def fill(image, mask):
@@ -123,8 +143,6 @@ MODELS = {
 COLORMAP = ['autumn', 'bone', 'jet', 'winter', 'rainbow', 'ocean', 'summer', 'spring', 'cool', 'hsv', 'pink', 'hot', 'parula', 'magma', 'inferno', 'plasma', 'viridis', 'cividis', 'twilight', 'shifted', 'turbo', 'deepgreen']
 cache_dir = 'models/control/segment'
 generator: MaskGenerationPipeline = None
-debug = shared.log.trace if os.environ.get('SD_MASK_DEBUG', None) is not None else lambda *args, **kwargs: None
-debug('Trace: MASK')
 busy = False
 btn_mask = None
 btn_lama = None

modules/processing_vae.py

@@ -44,8 +44,8 @@ def full_vae_decode(latents, model):
     upcast = (model.vae.dtype == torch.float16) and getattr(model.vae.config, 'force_upcast', False) and hasattr(model, 'upcast_vae')
     if upcast: # this is done by diffusers automatically if output_type != 'latent'
         model.upcast_vae()
-
-    latents = latents.to(next(iter(model.vae.post_quant_conv.parameters())).dtype)
+    if hasattr(model.vae, "post_quant_conv"):
+        latents = latents.to(next(iter(model.vae.post_quant_conv.parameters())).dtype)
     decoded = model.vae.decode(latents / model.vae.config.scaling_factor, return_dict=False)[0]
 
     # Delete PyTorch VAE after OpenVINO compile

modules/script_callbacks.py

@@ -9,7 +9,7 @@ import modules.errors as errors
 
 
 def report_exception(e, c, job):
-    errors.display(e, f'executing callback: {c.script} {job}')
+    errors.display(e, f'Executing callback: {c.script} {job}')
 
 
 class ImageSaveParams:

modules/scripts.py

@@ -362,49 +362,6 @@ class ScriptRunner:
             except Exception as e:
                 errors.log.error(f'Script initialize: {path} {e}')
 
-    """
-    def create_script_ui(self, script):
-        import modules.api.models as api_models
-        script.args_from = len(self.inputs)
-        script.args_to = len(self.inputs)
-        controls = wrap_call(script.ui, script.filename, "ui", script.is_img2img)
-        if controls is None:
-            return
-        script.name = wrap_call(script.title, script.filename, "title", default=script.filename).lower()
-        api_args = []
-        for control in controls:
-            if not isinstance(control, gr.components.IOComponent):
-                log.error(f'Invalid script control: "{script.filename}" control={control}')
-                continue
-            control.custom_script_source = os.path.basename(script.filename)
-            arg_info = api_models.ScriptArg(label=control.label or "")
-            for field in ("value", "minimum", "maximum", "step", "choices"):
-                v = getattr(control, field, None)
-                if v is not None:
-                    setattr(arg_info, field, v)
-            api_args.append(arg_info)
-        script.api_info = api_models.ScriptInfo(name=script.name, is_img2img=script.is_img2img, is_alwayson=script.alwayson, args=api_args)
-        if script.infotext_fields is not None:
-            self.infotext_fields += script.infotext_fields
-        if script.paste_field_names is not None:
-            self.paste_field_names += script.paste_field_names
-        self.inputs += controls
-        script.args_to = len(self.inputs)
-
-    def setup_ui_for_section(self, section, scriptlist=None):
-        if scriptlist is None:
-            scriptlist = self.alwayson_scripts
-        for script in scriptlist:
-            if script.alwayson and script.section != section:
-                continue
-            if script.create_group:
-                with gr.Group(visible=script.alwayson) as group:
-                    self.create_script_ui(script)
-                script.group = group
-            else:
-                self.create_script_ui(script)
-    """
-
     def prepare_ui(self):
         self.inputs = [None]
 
@@ -677,43 +634,3 @@ def reload_script_body_only():
     scripts_txt2img.reload_sources(cache)
     scripts_img2img.reload_sources(cache)
     scripts_control.reload_sources(cache)
-
-
-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
-    """
-    elem_classes = []
-    if hasattr(comp, "elem_classes"):
-        elem_classes = comp.elem_classes
-    if elem_classes is None:
-        elem_classes = []
-    comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])]
-    if getattr(comp, 'multiselect', False):
-        comp.elem_classes.append('multiselect')
-
-
-def IOComponent_init(self, *args, **kwargs):
-    if scripts_current is not None:
-        scripts_current.before_component(self, **kwargs)
-    script_callbacks.before_component_callback(self, **kwargs)
-    res = original_IOComponent_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
-    add_classes_to_gradio_component(self)
-    script_callbacks.after_component_callback(self, **kwargs)
-    if scripts_current is not None:
-        scripts_current.after_component(self, **kwargs)
-    return res
-
-
-original_IOComponent_init = gr.components.IOComponent.__init__
-gr.components.IOComponent.__init__ = IOComponent_init
-
-
-def BlockContext_init(self, *args, **kwargs):
-    res = original_BlockContext_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
-    add_classes_to_gradio_component(self)
-    return res
-
-
-original_BlockContext_init = gr.blocks.BlockContext.__init__
-gr.blocks.BlockContext.__init__ = BlockContext_init

modules/sd_models_compile.py

@@ -68,29 +68,39 @@ def ipex_optimize(sd_model):
 def nncf_compress_weights(sd_model):
     try:
         t0 = time.time()
+        if sd_model.device.type == "meta":
+            shared.log.warning("Compress Weights is not compatible with Sequential CPU offload")
+            return sd_model
+
+        def nncf_compress_model(model):
+            return_device = model.device
+            model = nncf.compress_weights(model.to(devices.device)).to(return_device)
+            devices.torch_gc(force=True)
+            return model
+
         import nncf
         shared.compiled_model_state = CompiledModelState()
         shared.compiled_model_state.is_compiled = True
 
         if "Model" in shared.opts.nncf_compress_weights:
             if hasattr(sd_model, 'unet') and hasattr(sd_model.unet, 'config'):
-                sd_model.unet = nncf.compress_weights(sd_model.unet)
+                sd_model.unet = nncf_compress_model(sd_model.unet)
             elif hasattr(sd_model, 'transformer') and hasattr(sd_model.transformer, 'config'):
-                sd_model.transformer = nncf.compress_weights(sd_model.transformer)
+                sd_model.transformer = nncf_compress_model(sd_model.transformer)
             else:
                 shared.log.warning('Compress Weights enabled but model has no Unet or Transformer')
         if "VAE" in shared.opts.nncf_compress_weights:
             if hasattr(sd_model, 'vae') and hasattr(sd_model.vae, 'decode'):
-                sd_model.vae = nncf.compress_weights(sd_model.vae)
+                sd_model.vae = nncf_compress_model(sd_model.vae)
             elif hasattr(sd_model, 'movq') and hasattr(sd_model.movq, 'decode'):
-                sd_model.movq = nncf.compress_weights(sd_model.movq)
+                sd_model.movq = nncf_compress_model(sd_model.movq)
             else:
                 shared.log.warning('Compress VAE Weights enabled but model has no VAE')
         if "Text Encoder" in shared.opts.nncf_compress_weights:
             if hasattr(sd_model, 'text_encoder') and hasattr(sd_model.text_encoder, 'config'):
-                sd_model.text_encoder = nncf.compress_weights(sd_model.text_encoder)
+                sd_model.text_encoder = nncf_compress_model(sd_model.text_encoder)
                 if hasattr(sd_model, 'text_encoder_2') and hasattr(sd_model.text_encoder_2, 'config'):
-                    sd_model.text_encoder_2 = nncf.compress_weights(sd_model.text_encoder_2)
+                    sd_model.text_encoder_2 = nncf_compress_model(sd_model.text_encoder_2)
             else:
                 shared.log.warning('Compress VAE Text Encoder Weights enabled but model has no Text Encoder')
         t1 = time.time()

modules/ui_common.py

@@ -6,16 +6,10 @@ import platform
 import subprocess
 from functools import reduce
 import gradio as gr
-from modules import call_queue, shared, prompt_parser
-from modules import generation_parameters_copypaste
-from modules import ui_sections
-from modules.ui_components import ToolButton
-import modules.ui_symbols as symbols
-import modules.images
-import modules.script_callbacks
+from modules import call_queue, shared, prompt_parser, ui_sections, ui_symbols, ui_components, generation_parameters_copypaste, images, scripts, script_callbacks
 
 
-folder_symbol = symbols.folder
+folder_symbol = ui_symbols.folder
 debug = shared.log.trace if os.environ.get('SD_PASTE_DEBUG', None) is not None else lambda *args, **kwargs: None
 debug('Trace: PASTE')
 
@@ -58,19 +52,19 @@ def infotext_to_html(text):
     return code
 
 
-def delete_files(js_data, images, _html_info, index):
+def delete_files(js_data, files, _html_info, index):
     try:
         data = json.loads(js_data)
     except Exception:
         data = { 'index_of_first_image': 0 }
     start_index = 0
     if index > -1 and shared.opts.save_selected_only and (index >= data['index_of_first_image']):
-        images = [images[index]]
+        files = [files[index]]
         start_index = index
         filenames = []
     filenames = []
     fullfns = []
-    for _image_index, filedata in enumerate(images, start_index):
+    for _image_index, filedata in enumerate(files, start_index):
         if 'name' in filedata and os.path.isfile(filedata['name']):
             fullfn = filedata['name']
             filenames.append(os.path.basename(fullfn))
@@ -84,11 +78,11 @@ def delete_files(js_data, images, _html_info, index):
                 shared.log.info(f"Deleting image: {fullfn}")
             except Exception as e:
                 shared.log.error(f'Error deleting file: {fullfn} {e}')
-    images = [image for image in images if image['name'] not in fullfns]
-    return images, plaintext_to_html(f"Deleted: {filenames[0] if len(filenames) > 0 else 'none'}")
+    files = [image for image in files if image['name'] not in fullfns]
+    return files, plaintext_to_html(f"Deleted: {filenames[0] if len(filenames) > 0 else 'none'}")
 
 
-def save_files(js_data, images, html_info, index):
+def save_files(js_data, files, html_info, index):
     os.makedirs(shared.opts.outdir_save, exist_ok=True)
 
     class PObject: # pylint: disable=too-few-public-methods
@@ -117,11 +111,11 @@ def save_files(js_data, images, html_info, index):
     p = PObject(data)
     start_index = 0
     if index > -1 and shared.opts.save_selected_only and (index >= p.index_of_first_image):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only # pylint: disable=no-member
-        images = [images[index]]
+        files = [files[index]]
         start_index = index
     filenames = []
     fullfns = []
-    for image_index, filedata in enumerate(images, start_index):
+    for image_index, filedata in enumerate(files, start_index):
         is_grid = image_index < p.index_of_first_image # pylint: disable=no-member
         i = 0 if is_grid else (image_index - p.index_of_first_image) # pylint: disable=no-member
         while len(p.all_seeds) <= i:
@@ -135,7 +129,7 @@ def save_files(js_data, images, html_info, index):
             filenames.append(os.path.basename(fullfn))
             fullfns.append(fullfn)
             destination = shared.opts.outdir_save
-            namegen = modules.images.FilenameGenerator(p, seed=p.all_seeds[i], prompt=p.all_prompts[i], image=None)  # pylint: disable=no-member
+            namegen = images.FilenameGenerator(p, seed=p.all_seeds[i], prompt=p.all_prompts[i], image=None)  # pylint: disable=no-member
             dirname = namegen.apply(shared.opts.directories_filename_pattern or "[prompt_words]").lstrip(' ').rstrip('\\ /')
             destination = os.path.join(destination, dirname)
             destination = namegen.sanitize(destination)
@@ -154,11 +148,11 @@ def save_files(js_data, images, html_info, index):
                     shared.log.debug(f'Saving: text="{filename_txt}"')
                 except Exception as e:
                     shared.log.warning(f'Image description save failed: {filename_txt} {e}')
-            modules.script_callbacks.image_save_btn_callback(tgt_filename)
+            script_callbacks.image_save_btn_callback(tgt_filename)
         else:
             image = generation_parameters_copypaste.image_from_url_text(filedata)
             info = p.infotexts[i + 1] if len(p.infotexts) > len(p.all_seeds) else p.infotexts[i] # infotexts may be offset by 1 because the first image is the grid
-            fullfn, txt_fullfn = modules.images.save_image(image, shared.opts.outdir_save, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], info=info, extension=shared.opts.samples_format, grid=is_grid, p=p)
+            fullfn, txt_fullfn = images.save_image(image, shared.opts.outdir_save, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], info=info, extension=shared.opts.samples_format, grid=is_grid, p=p)
             if fullfn is None:
                 continue
             filename = os.path.relpath(fullfn, shared.opts.outdir_save)
@@ -167,7 +161,7 @@ def save_files(js_data, images, html_info, index):
             if txt_fullfn:
                 filenames.append(os.path.basename(txt_fullfn))
                 # fullfns.append(txt_fullfn)
-            modules.script_callbacks.image_save_btn_callback(filename)
+            script_callbacks.image_save_btn_callback(filename)
     if shared.opts.samples_save_zip and len(fullfns) > 1:
         zip_filepath = os.path.join(shared.opts.outdir_save, "images.zip")
         from zipfile import ZipFile
@@ -277,11 +271,11 @@ def create_output_panel(tabname, preview=True, prompt=None, height=None):
                 )
 
             if tabname == "txt2img":
-                paste_field_names = modules.scripts.scripts_txt2img.paste_field_names
+                paste_field_names = scripts.scripts_txt2img.paste_field_names
             elif tabname == "img2img":
-                paste_field_names = modules.scripts.scripts_img2img.paste_field_names
+                paste_field_names = scripts.scripts_img2img.paste_field_names
             elif tabname == "control":
-                paste_field_names = modules.scripts.scripts_control.paste_field_names
+                paste_field_names = scripts.scripts_control.paste_field_names
             else:
                 paste_field_names = []
             for paste_tabname, paste_button in buttons.items():
@@ -299,7 +293,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
             setattr(refresh_component, k, v)
         return gr.update(**(args or {}))
 
-    refresh_button = ToolButton(value=symbols.refresh, elem_id=elem_id, visible=visible)
+    refresh_button = ui_components.ToolButton(value=ui_symbols.refresh, elem_id=elem_id, visible=visible)
     refresh_button.click(fn=refresh, inputs=[], outputs=[refresh_component])
     return refresh_button
 
@@ -311,7 +305,7 @@ def create_browse_button(browse_component, elem_id):
             return gr.update(value = folder)
         return gr.update()
 
-    browse_button = ToolButton(value=symbols.folder, elem_id=elem_id)
+    browse_button = ui_components.ToolButton(value=ui_symbols.folder, elem_id=elem_id)
     browse_button.click(fn=browse, _js="async () => await browseFolder()", inputs=[browse_component], outputs=[browse_component])
     # browse_button.click(fn=browse, inputs=[browse_component], outputs=[browse_component])
     return browse_button
@@ -352,33 +346,30 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 
 
 def update_token_counter(text, steps):
-    from modules import extra_networks, sd_hijack
+    token_count = 0
+    max_length = 75
+    if shared.state.job_count > 0:
+        shared.log.info('Tokenizer busy')
+        return f"<span class='gr-box gr-text-input'>{token_count}/{max_length}</span>"
+    from modules import extra_networks
     try:
         text, _ = extra_networks.parse_prompt(text)
         _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
     except Exception:
         prompt_schedules = [[[steps, text]]]
-
     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
     prompts = [prompt_text for step, prompt_text in flat_prompts]
     if shared.backend == shared.Backend.ORIGINAL:
+        from modules import sd_hijack
         token_count, max_length = max([sd_hijack.model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
     elif shared.backend == shared.Backend.DIFFUSERS:
-        if shared.sd_model is not None and hasattr(shared.sd_model, 'tokenizer'):
-            tokenizer = shared.sd_model.tokenizer
-            if tokenizer is None:
-                token_count = 0
-                max_length = 75
-            else:
-                has_bos_token = tokenizer.bos_token_id is not None
-                has_eos_token = tokenizer.eos_token_id is not None
-                ids = [shared.sd_model.tokenizer(prompt) for prompt in prompts]
-                if len(ids) > 0 and hasattr(ids[0], 'input_ids'):
-                    ids = [x.input_ids for x in ids]
-                token_count = max([len(x) for x in ids]) - int(has_bos_token) - int(has_eos_token)
-                max_length = tokenizer.model_max_length - int(has_bos_token) - int(has_eos_token)
-        else:
-            token_count = 0
-            max_length = 75
+        if shared.sd_model is not None and hasattr(shared.sd_model, 'tokenizer') and shared.sd_model.tokenizer is not None:
+            has_bos_token = shared.sd_model.tokenizer.bos_token_id is not None
+            has_eos_token = shared.sd_model.tokenizer.eos_token_id is not None
+            ids = [shared.sd_model.tokenizer(prompt) for prompt in prompts]
+            if len(ids) > 0 and hasattr(ids[0], 'input_ids'):
+                ids = [x.input_ids for x in ids]
+            token_count = max([len(x) for x in ids]) - int(has_bos_token) - int(has_eos_token)
+            max_length = shared.sd_model.tokenizer.model_max_length - int(has_bos_token) - int(has_eos_token)
     return f"<span class='gr-box gr-text-input'>{token_count}/{max_length}</span>"

webui.py

@@ -13,7 +13,7 @@ import torch # pylint: disable=wrong-import-order
 from modules import timer, errors, paths # pylint: disable=unused-import
 from installer import log, git_commit, custom_excepthook
 import ldm.modules.encoders.modules # pylint: disable=W0611,C0411,E0401
-from modules import shared, extensions, ui_tempdir, modelloader # pylint: disable=ungrouped-imports
+from modules import shared, extensions, gr_tempdir, modelloader # pylint: disable=ungrouped-imports
 from modules import extra_networks, ui_extra_networks # pylint: disable=ungrouped-imports
 from modules.paths import create_paths
 from modules.call_queue import queue_lock, wrap_queued_call, wrap_gradio_gpu_call # pylint: disable=W0611,C0411,C0412
@@ -111,7 +111,7 @@ def initialize():
     timer.startup.record("upscalers")
 
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-    shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
+    shared.opts.onchange("temp_dir", gr_tempdir.on_tmpdir_changed)
     timer.startup.record("onchange")
 
     modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
@@ -212,7 +212,7 @@ def start_common():
     async_policy()
     initialize()
     if shared.opts.clean_temp_dir_at_start:
-        ui_tempdir.cleanup_tmpdr()
+        gr_tempdir.cleanup_tmpdr()
         timer.startup.record("cleanup")
 
 
@@ -269,7 +269,7 @@ def start_ui():
             _frontend=True and cmd_opts.share,
         )
     if cmd_opts.data_dir is not None:
-        ui_tempdir.register_tmp_file(shared.demo, os.path.join(cmd_opts.data_dir, 'x'))
+        gr_tempdir.register_tmp_file(shared.demo, os.path.join(cmd_opts.data_dir, 'x'))
     shared.log.info(f'Local URL: {local_url}')
     if cmd_opts.docs:
         shared.log.info(f'API Docs: {local_url[:-1]}/docs') # pylint: disable=unsubscriptable-object