Merge branch 'master' into master

1 files changed, 104 insertions, 37 deletions

diff --git a/modules/shared.py b/modules/shared.py
index ac968b2d..aa69bedf 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -12,12 +12,13 @@ import modules.interrogate
 import modules.memmon

 import modules.sd_models

 import modules.styles

-from modules.devices import get_optimal_device

-from modules.paths import script_path, sd_path

+import modules.devices as devices

+from modules import sd_samplers, sd_models

+from modules.hypernetworks import hypernetwork

+from modules.paths import models_path, script_path, sd_path

 

 sd_model_file = os.path.join(script_path, 'model.ckpt')

 default_sd_model_file = sd_model_file

-model_path = os.path.join(script_path, 'models')

 parser = argparse.ArgumentParser()

 parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs/stable-diffusion/v1-inference.yaml"), help="path to config which constructs model",)

 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)

@@ -25,26 +26,36 @@ parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to director
 parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))

 parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None)

 parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats")

+parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats")

 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")

 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")

 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")

+parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")

 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")

 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")

 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")

+parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM")

 parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")

 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")

 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")

 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")

-parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(model_path, 'Codeformer'))

-parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(model_path, 'GFPGAN'))

-parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(model_path, 'ESRGAN'))

-parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(model_path, 'BSRGAN'))

-parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(model_path, 'RealESRGAN'))

-parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(model_path, 'SwinIR'))

-parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(model_path, 'LDSR'))

-parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")

-parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")

+parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)

+parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))

+parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))

+parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))

+parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(models_path, 'BSRGAN'))

+parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(models_path, 'RealESRGAN'))

+parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET'))

+parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))

+parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))

+parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")

+parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")

+parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")

+parser.add_argument("--opt-split-attention", action='store_true', help="force-enables Doggettx's cross-attention layer optimization. By default, it's on for torch cuda.")

+parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")

 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")

+parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")

+parser.add_argument("--use-cpu", nargs='+',choices=['all', 'sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'], help="use CPU as torch device for specified modules", default=[], type=str.lower)

 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")

 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)

 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)

@@ -53,21 +64,44 @@ parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide dire
 parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))

 parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")

 parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)

+parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor")

 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")

 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))

 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)

 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)

+parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)

+parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)

+parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencoders model', default=None)

+parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)

+

 

 cmd_opts = parser.parse_args()

-device = get_optimal_device()

+

+devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \

+(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'])

+

+device = devices.device

+weight_load_location = None if cmd_opts.lowram else "cpu"

 

 batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)

 parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram

-

+xformers_available = False

 config_filename = cmd_opts.ui_settings_file

 

+os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)

+hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)

+loaded_hypernetwork = None

+

+

+def reload_hypernetworks():

+    global hypernetworks

+

+    hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)

+    hypernetwork.load_hypernetwork(opts.sd_hypernetwork)

+

 

 class State:

+    skipped = False

     interrupted = False

     job = ""

     job_no = 0

@@ -78,6 +112,10 @@ class State:
     current_latent = None

     current_image = None

     current_image_sampling_step = 0

+    textinfo = None

+

+    def skip(self):

+        self.skipped = True

 

     def interrupt(self):

         self.interrupted = True

@@ -88,7 +126,7 @@ class State:
         self.current_image_sampling_step = 0

         

     def get_job_timestamp(self):

-        return datetime.datetime.now().strftime("%Y%m%d%H%M%S")

+        return datetime.datetime.now().strftime("%Y%m%d%H%M%S")  # shouldn't this return job_timestamp?

 

 

 state = State()

@@ -101,8 +139,6 @@ prompt_styles = modules.styles.StyleDatabase(styles_filename)
 interrogator = modules.interrogate.InterrogateModels("interrogate")

 

 face_restorers = []

-# This was moved to webui.py with the other model "setup" calls.

-# modules.sd_models.list_models()

 

 

 def realesrgan_models_names():

@@ -111,18 +147,19 @@ def realesrgan_models_names():
 

 

 class OptionInfo:

-    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None):

+    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False, refresh=None):

         self.default = default

         self.label = label

         self.component = component

         self.component_args = component_args

         self.onchange = onchange

         self.section = None

+        self.refresh = refresh

 

 

-def options_section(section_identifer, options_dict):

+def options_section(section_identifier, options_dict):

     for k, v in options_dict.items():

-        v.section = section_identifer

+        v.section = section_identifier

 

     return options_dict

 

@@ -140,6 +177,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "grid_format": OptionInfo('png', 'File format for grids'),

     "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),

     "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),

+    "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"),

     "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}),

 

     "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),

@@ -150,6 +188,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
 

     "use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process in extras tab"),

     "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),

+    "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),

 }))

 

 options_templates.update(options_section(('saving-paths', "Paths for saving"), {

@@ -165,9 +204,10 @@ options_templates.update(options_section(('saving-paths', "Paths for saving"), {
 

 options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {

     "save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),

-    "grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"),

+    "grid_save_to_dirs": OptionInfo(False, "Save grids to a subdirectory"),

+    "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),

     "directories_filename_pattern": OptionInfo("", "Directory name pattern"),

-    "directories_max_prompt_words": OptionInfo(8, "Max prompt words", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),

+    "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),

 }))

 

 options_templates.update(options_section(('upscaling', "Upscaling"), {

@@ -177,7 +217,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
     "SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),

     "SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),

     "ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),

-    "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Radio, lambda: {"choices": [x.name for x in sd_upscalers]}),

+    "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),

 }))

 

 options_templates.update(options_section(('face-restoration', "Face restoration"), {

@@ -189,50 +229,75 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
 options_templates.update(options_section(('system', "System"), {

     "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),

     "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),

-    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),

+    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),

+}))

+

+options_templates.update(options_section(('training', "Training"), {

+    "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"),

+    "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),

+    "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),

+    "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),

+    "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"),

 }))

 

 options_templates.update(options_section(('sd', "Stable Diffusion"), {

-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),

+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),

+    "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),

+    "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),

+    "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),

     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),

     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),

     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),

     "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),

-    "enable_emphasis": OptionInfo(True, "Eemphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),

+    "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),

     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),

     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),

+    "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),

     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),

+    'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),

     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),

+    'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"),

 }))

 

 options_templates.update(options_section(('interrogate', "Interrogate Options"), {

     "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_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),

     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),

     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),

     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),

-    "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"),

+    "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: 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}),

+    "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),

+    "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),

+    "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),

 }))

 

 options_templates.update(options_section(('ui', "User interface"), {

     "show_progressbar": OptionInfo(True, "Show progressbar"),

-    "show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),

+    "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),

     "return_grid": OptionInfo(True, "Show grid in results for web"),

+    "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),

     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),

+    "add_model_name_to_info": OptionInfo(False, "Add model name to generation information"),

     "font": OptionInfo("", "Font for image grids that have text"),

     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),

-    "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),

+    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),

+    "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),

 }))

 

 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {

-  "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

-  "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

-  "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),

-  's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

-  's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

-  's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in sd_samplers.all_samplers]}),

+    "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),

+    's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),

+    'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),

 }))

 

+

 class Options:

     data = None

     data_labels = options_templates

@@ -289,6 +354,8 @@ class Options:
         item = self.data_labels.get(key)

         item.onchange = func

 

+        func()

+

     def dumpjson(self):

         d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()}

         return json.dumps(d)

@@ -318,14 +385,14 @@ class TotalTQDM:
         )

 

     def update(self):

-        if not opts.multiple_tqdm:

+        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:

             return

         if self._tqdm is None:

             self.reset()

         self._tqdm.update()

 

     def updateTotal(self, new_total):

-        if not opts.multiple_tqdm:

+        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:

             return

         if self._tqdm is None:

             self.reset()