From 313e14de04d9955c6ad077341feceb0fc7f2f1d3 Mon Sep 17 00:00:00 2001
From: Chris OBryan <13701027+cobryan05@users.noreply.github.com>
Date: Wed, 2 Nov 2022 21:37:43 -0500
Subject: extras - skip unnecessary second hash of image

There is no need to re-hash the input image each iteration of the loop.
This also reverts PR #4026 as it was determined the cache hits it avoids
were actually valid.
---
 modules/extras.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 8e2ab35c..71b93a06 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -136,12 +136,13 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
 
     def run_upscalers_blend(params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]:
         blended_result: Image.Image = None
+        image_hash: str = hash(np.array(image.getdata()).tobytes())
         for upscaler in params:
             upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode,
                             upscaling_resize_w, upscaling_resize_h, upscaling_crop)
-            cache_key = LruCache.Key(image_hash=hash(np.array(image.getdata()).tobytes()),
+            cache_key = LruCache.Key(image_hash=image_hash,
                                      info_hash=hash(info),
-                                     args_hash=hash((upscale_args, upscale_first)))
+                                     args_hash=hash(upscale_args))
             cached_entry = cached_images.get(cache_key)
             if cached_entry is None:
                 res = upscale(image, *upscale_args)
-- 
cgit v1.2.3


From 904121fecc0a1f11db76a73ca8649fb21e05ac5b Mon Sep 17 00:00:00 2001
From: Nandaka <nchek2000@gmail.com>
Date: Thu, 24 Nov 2022 02:39:09 +0000
Subject: Support NAI exif for PNG Info

---
 modules/extras.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 71b93a06..af4cd97d 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -233,6 +233,20 @@ def run_pnginfo(image):
 
     geninfo = items.get('parameters', geninfo)
 
+    # nai prompt
+    if "Software" in items.keys() and items["Software"] == "NovelAI":
+        import json
+        json_info = json.loads(items["Comment"])
+        geninfo = f'{items["Description"]}\r\nNegative prompt: {json_info["uc"]}\r\n'
+        sampler = "Euler a"
+        if json_info["sampler"] == "k_euler_ancestral":
+            sampler = "Euler a"
+        elif json_info["sampler"] == "k_euler":
+            sampler = "Euler"
+        model_hash = '925997e9'  # assuming this is the correct model hash
+        # not sure with noise and strength parameter
+        geninfo += f'Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Model hash: {model_hash}'  # , Denoising strength: {json_info["noise"]}'
+
     info = ''
     for key, text in items.items():
         info += f"""
-- 
cgit v1.2.3


From dac9b6f15de5e675053d9490a20e0457dcd1a23e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 27 Nov 2022 15:51:29 +0300
Subject: add safetensors support for model merging #4869

---
 modules/extras.py    | 26 ++++++++++++++------------
 modules/sd_models.py | 26 +++++++++++++++-----------
 modules/ui.py        |  7 ++++++-
 3 files changed, 35 insertions(+), 24 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 71b93a06..3d65d90a 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -20,6 +20,7 @@ import modules.codeformer_model
 import piexif
 import piexif.helper
 import gradio as gr
+import safetensors.torch
 
 
 class LruCache(OrderedDict):
@@ -249,7 +250,7 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name):
+def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
@@ -264,19 +265,15 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
     teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
 
     print(f"Loading {primary_model_info.filename}...")
-    primary_model = torch.load(primary_model_info.filename, map_location='cpu')
-    theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
+    theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
 
     print(f"Loading {secondary_model_info.filename}...")
-    secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
-    theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)
+    theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
 
     if teritary_model_info is not None:
         print(f"Loading {teritary_model_info.filename}...")
-        teritary_model = torch.load(teritary_model_info.filename, map_location='cpu')
-        theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model)
+        theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu')
     else:
-        teritary_model = None
         theta_2 = None
 
     theta_funcs = {
@@ -295,7 +292,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
                     theta_1[key] = theta_func1(theta_1[key], t2)
                 else:
                     theta_1[key] = torch.zeros_like(theta_1[key])
-    del theta_2, teritary_model
+    del theta_2
 
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
@@ -314,12 +311,17 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
-    filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
-    filename = filename if custom_name == '' else (custom_name + '.ckpt')
+    filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.' + checkpoint_format
+    filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format)
     output_modelname = os.path.join(ckpt_dir, filename)
 
     print(f"Saving to {output_modelname}...")
-    torch.save(primary_model, output_modelname)
+
+    _, extension = os.path.splitext(output_modelname)
+    if extension.lower() == ".safetensors":
+        safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"})
+    else:
+        torch.save(theta_0, output_modelname)
 
     sd_models.list_models()
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 77236480..a1ea5611 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -160,6 +160,20 @@ def get_state_dict_from_checkpoint(pl_sd):
     return pl_sd
 
 
+def read_state_dict(checkpoint_file, print_global_state=False, map_location=None):
+    _, extension = os.path.splitext(checkpoint_file)
+    if extension.lower() == ".safetensors":
+        pl_sd = safetensors.torch.load_file(checkpoint_file, device=map_location or shared.weight_load_location)
+    else:
+        pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
+
+    if print_global_state and "global_step" in pl_sd:
+        print(f"Global Step: {pl_sd['global_step']}")
+
+    sd = get_state_dict_from_checkpoint(pl_sd)
+    return sd
+
+
 def load_model_weights(model, checkpoint_info, vae_file="auto"):
     checkpoint_file = checkpoint_info.filename
     sd_model_hash = checkpoint_info.hash
@@ -174,17 +188,7 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
         # load from file
         print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
 
-        _, extension = os.path.splitext(checkpoint_file)
-        if extension.lower() == ".safetensors":
-            pl_sd = safetensors.torch.load_file(checkpoint_file, device=shared.weight_load_location)
-        else:
-            pl_sd = torch.load(checkpoint_file, map_location=shared.weight_load_location)
-
-        if "global_step" in pl_sd:
-            print(f"Global Step: {pl_sd['global_step']}")
-
-        sd = get_state_dict_from_checkpoint(pl_sd)
-        del pl_sd
+        sd = read_state_dict(checkpoint_file)
         model.load_state_dict(sd, strict=False)
         del sd
         
diff --git a/modules/ui.py b/modules/ui.py
index de2b5544..aa13978d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1164,7 +1164,11 @@ def create_ui(wrap_gradio_gpu_call):
                 custom_name = gr.Textbox(label="Custom Name (Optional)")
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)
                 interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")
-                save_as_half = gr.Checkbox(value=False, label="Save as float16")
+
+                with gr.Row():
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format")
+                    save_as_half = gr.Checkbox(value=False, label="Save as float16")
+
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
 
             with gr.Column(variant='panel'):
@@ -1692,6 +1696,7 @@ def create_ui(wrap_gradio_gpu_call):
                 interp_amount,
                 save_as_half,
                 custom_name,
+                checkpoint_format,
             ],
             outputs=[
                 submit_result,
-- 
cgit v1.2.3


From 506d529d19f135f57e142371271f84d4971b456f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 27 Nov 2022 16:28:32 +0300
Subject: rework #5012 to also work for pictures dragged into the prompt and
 also add Clip skip + ENSD to parameters

---
 modules/extras.py                          | 40 ++++--------------------------
 modules/generation_parameters_copypaste.py |  1 +
 modules/images.py                          | 38 +++++++++++++++++++++++++++-
 modules/sd_samplers.py                     |  2 +-
 4 files changed, 44 insertions(+), 37 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 0057bf9c..6021a024 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -1,6 +1,8 @@
 from __future__ import annotations
 import math
 import os
+import sys
+import traceback
 
 import numpy as np
 from PIL import Image
@@ -12,7 +14,7 @@ from typing import Callable, List, OrderedDict, Tuple
 from functools import partial
 from dataclasses import dataclass
 
-from modules import processing, shared, images, devices, sd_models
+from modules import processing, shared, images, devices, sd_models, sd_samplers
 from modules.shared import opts
 import modules.gfpgan_model
 from modules.ui import plaintext_to_html
@@ -22,7 +24,6 @@ import piexif.helper
 import gradio as gr
 import safetensors.torch
 
-
 class LruCache(OrderedDict):
     @dataclass(frozen=True)
     class Key:
@@ -214,39 +215,8 @@ def run_pnginfo(image):
     if image is None:
         return '', '', ''
 
-    items = image.info
-    geninfo = ''
-
-    if "exif" in image.info:
-        exif = piexif.load(image.info["exif"])
-        exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
-        try:
-            exif_comment = piexif.helper.UserComment.load(exif_comment)
-        except ValueError:
-            exif_comment = exif_comment.decode('utf8', errors="ignore")
-
-        items['exif comment'] = exif_comment
-        geninfo = exif_comment
-
-        for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
-                      'loop', 'background', 'timestamp', 'duration']:
-            items.pop(field, None)
-
-    geninfo = items.get('parameters', geninfo)
-
-    # nai prompt
-    if "Software" in items.keys() and items["Software"] == "NovelAI":
-        import json
-        json_info = json.loads(items["Comment"])
-        geninfo = f'{items["Description"]}\r\nNegative prompt: {json_info["uc"]}\r\n'
-        sampler = "Euler a"
-        if json_info["sampler"] == "k_euler_ancestral":
-            sampler = "Euler a"
-        elif json_info["sampler"] == "k_euler":
-            sampler = "Euler"
-        model_hash = '925997e9'  # assuming this is the correct model hash
-        # not sure with noise and strength parameter
-        geninfo += f'Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Model hash: {model_hash}'  # , Denoising strength: {json_info["noise"]}'
+    geninfo, items = images.read_info_from_image(image)
+    items = {**{'parameters': geninfo}, **items}
 
     info = ''
     for key, text in items.items():
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 1408ea05..0973c695 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -75,6 +75,7 @@ def integrate_settings_paste_fields(component_dict):
         'CLIP_stop_at_last_layers': 'Clip skip',
         'inpainting_mask_weight': 'Conditional mask weight',
         'sd_model_checkpoint': 'Model hash',
+        'eta_noise_seed_delta': 'ENSD',
     }
     settings_paste_fields = [
         (component_dict[k], lambda d, k=k, v=v: ui.apply_setting(k, d.get(v, None)))
diff --git a/modules/images.py b/modules/images.py
index b968d6a6..08a72e67 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -15,6 +15,7 @@ import piexif.helper
 from PIL import Image, ImageFont, ImageDraw, PngImagePlugin
 from fonts.ttf import Roboto
 import string
+import json
 
 from modules import sd_samplers, shared, script_callbacks
 from modules.shared import opts, cmd_opts
@@ -553,10 +554,45 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     return fullfn, txt_fullfn
 
 
+def read_info_from_image(image):
+    items = image.info or {}
+
+    geninfo = items.pop('parameters', None)
+
+    if "exif" in items:
+        exif = piexif.load(items["exif"])
+        exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
+        try:
+            exif_comment = piexif.helper.UserComment.load(exif_comment)
+        except ValueError:
+            exif_comment = exif_comment.decode('utf8', errors="ignore")
+
+        items['exif comment'] = exif_comment
+        geninfo = exif_comment
+
+        for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
+                      'loop', 'background', 'timestamp', 'duration']:
+            items.pop(field, None)
+
+    if items.get("Software", None) == "NovelAI":
+        try:
+            json_info = json.loads(items["Comment"])
+            sampler = sd_samplers.samplers_map.get(json_info["sampler"], "Euler a")
+
+            geninfo = f"""{items["Description"]}
+Negative prompt: {json_info["uc"]}
+Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337"""
+        except Exception:
+            print(f"Error parsing NovelAI iamge generation parameters:", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+
+    return geninfo, items
+
+
 def image_data(data):
     try:
         image = Image.open(io.BytesIO(data))
-        textinfo = image.text["parameters"]
+        textinfo, _ = read_info_from_image(image)
         return textinfo, None
     except Exception:
         pass
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 2ca17d8b..5fefb227 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -18,7 +18,7 @@ from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
 
 samplers_k_diffusion = [
-    ('Euler a', 'sample_euler_ancestral', ['k_euler_a'], {}),
+    ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}),
     ('Euler', 'sample_euler', ['k_euler'], {}),
     ('LMS', 'sample_lms', ['k_lms'], {}),
     ('Heun', 'sample_heun', ['k_heun'], {}),
-- 
cgit v1.2.3


From 44c46f0ed395967cd3830dd481a2db759fda5b3b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 4 Dec 2022 12:30:44 +0300
Subject: make it possible to merge inpainting model with non-inpainting one

---
 modules/extras.py | 27 +++++++++++++++++++++++++--
 1 file changed, 25 insertions(+), 2 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 6021a024..bc349d5e 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -247,6 +247,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
     primary_model_info = sd_models.checkpoints_list[primary_model_name]
     secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
     teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
+    result_is_inpainting_model = False
 
     print(f"Loading {primary_model_info.filename}...")
     theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
@@ -280,8 +281,22 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
+            a = theta_0[key]
+            b = theta_1[key]
 
-            theta_0[key] = theta_func2(theta_0[key], theta_1[key], multiplier)
+            # this enables merging an inpainting model (A) with another one (B);
+            # where normal model would have 4 channels, for latenst space, inpainting model would
+            # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
+            if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]:
+                if a.shape[1] == 4 and b.shape[1] == 9:
+                    raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")
+
+                assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"
+
+                theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
+                result_is_inpainting_model = True
+            else:
+                theta_0[key] = theta_func2(a, b, multiplier)
 
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
@@ -295,8 +310,16 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
-    filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.' + checkpoint_format
+    filename = \
+        primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + \
+        secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + \
+        interp_method.replace(" ", "_") + \
+        '-merged.' +  \
+        ("inpainting." if result_is_inpainting_model else "") + \
+        checkpoint_format
+
     filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format)
+
     output_modelname = os.path.join(ckpt_dir, filename)
 
     print(f"Saving to {output_modelname}...")
-- 
cgit v1.2.3


From 681c450ecd8f0999cbaf562c5e734c7105320ad9 Mon Sep 17 00:00:00 2001
From: Mackerel <mackerel@chickatrice.com>
Date: Sun, 4 Dec 2022 01:13:36 -0500
Subject: extras.py: use as little RAM as possible, misc fixes

maximum of 2 models loaded at once. delete unneeded model before next
step. fix 'teritary' -> 'tertiary'. gracefully fail when "add
difference" is selected without a tertiary model
---
 modules/extras.py | 37 +++++++++++++++++++------------------
 1 file changed, 19 insertions(+), 18 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index bc349d5e..0ad8deec 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -62,7 +62,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
     # Also keep track of original file names
     imageNameArr = []
     outputs = []
-    
+
     if extras_mode == 1:
         #convert file to pillow image
         for img in image_folder:
@@ -234,7 +234,7 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
+def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
@@ -246,30 +246,25 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     primary_model_info = sd_models.checkpoints_list[primary_model_name]
     secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
-    teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
+    tertiary_model_info = sd_models.checkpoints_list.get(tertiary_model_name, None)
     result_is_inpainting_model = False
 
-    print(f"Loading {primary_model_info.filename}...")
-    theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
-
-    print(f"Loading {secondary_model_info.filename}...")
-    theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
-
-    if teritary_model_info is not None:
-        print(f"Loading {teritary_model_info.filename}...")
-        theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu')
-    else:
-        theta_2 = None
-
     theta_funcs = {
         "Weighted sum": (None, weighted_sum),
         "Add difference": (get_difference, add_difference),
     }
     theta_func1, theta_func2 = theta_funcs[interp_method]
 
-    print(f"Merging...")
+    if theta_func1 and not tertiary_model_info:
+        return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
+
+    print(f"Loading {secondary_model_info.filename}...")
+    theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
 
     if theta_func1:
+        print(f"Loading {tertiary_model_info.filename}...")
+        theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
+
         for key in tqdm.tqdm(theta_1.keys()):
             if 'model' in key:
                 if key in theta_2:
@@ -277,7 +272,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
                     theta_1[key] = theta_func1(theta_1[key], t2)
                 else:
                     theta_1[key] = torch.zeros_like(theta_1[key])
-    del theta_2
+        del theta_2
+
+    print(f"Loading {primary_model_info.filename}...")
+    theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
+
+    print("Merging...")
 
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
@@ -307,6 +307,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
             theta_0[key] = theta_1[key]
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
+    del theta_1
 
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
@@ -332,5 +333,5 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     sd_models.list_models()
 
-    print(f"Checkpoint saved.")
+    print("Checkpoint saved.")
     return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
-- 
cgit v1.2.3


From 957e15c4642199e0792eba817a15e244246fb012 Mon Sep 17 00:00:00 2001
From: Yuval Aboulafia <yuval.abou@gmail.com>
Date: Wed, 14 Dec 2022 20:59:33 +0200
Subject: Correct singleton comparisons

---
 modules/extras.py | 2 +-
 modules/ngrok.py  | 4 ++--
 modules/ui.py     | 8 ++++++--
 3 files changed, 9 insertions(+), 5 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 0ad8deec..69b85465 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -188,7 +188,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         for op in extras_ops:
             image, info = op(image, info)
 
-        if opts.use_original_name_batch and image_name != None:
+        if opts.use_original_name_batch and image_name is not None:
             basename = os.path.splitext(os.path.basename(image_name))[0]
         else:
             basename = ''
diff --git a/modules/ngrok.py b/modules/ngrok.py
index 64c9a3c2..3df2c06b 100644
--- a/modules/ngrok.py
+++ b/modules/ngrok.py
@@ -2,7 +2,7 @@ from pyngrok import ngrok, conf, exception
 
 def connect(token, port, region):
     account = None
-    if token == None:
+    if token is None:
         token = 'None'
     else:
         if ':' in token:
@@ -14,7 +14,7 @@ def connect(token, port, region):
         auth_token=token, region=region
     )
     try:
-        if account == None:
+        if account is None:
             public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url
         else:
             public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True, auth=account).public_url
diff --git a/modules/ui.py b/modules/ui.py
index 28481e33..c4bb186d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -49,10 +49,14 @@ if not cmd_opts.share and not cmd_opts.listen:
     gradio.utils.version_check = lambda: None
     gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
 
-if cmd_opts.ngrok != None:
+if cmd_opts.ngrok is not None:
     import modules.ngrok as ngrok
     print('ngrok authtoken detected, trying to connect...')
-    ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860, cmd_opts.ngrok_region)
+    ngrok.connect(
+        cmd_opts.ngrok,
+        cmd_opts.port if cmd_opts.port is not None else 7860,
+        cmd_opts.ngrok_region
+        )
 
 
 def gr_show(visible=True):
-- 
cgit v1.2.3


From a26fe85056cf0dacef2d78cccf6ab100fd16da1c Mon Sep 17 00:00:00 2001
From: timntorres <timothynarcisotorres@gmail.com>
Date: Sat, 17 Dec 2022 04:31:03 -0800
Subject: Add upscaler name as a suffix.

---
 modules/extras.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index bc349d5e..9b60e360 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -193,8 +193,13 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         else:
             basename = ''
 
+        # Add upscaler name as a suffix.
+        suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}"
+        if extras_upscaler_2 and extras_upscaler_2_visibility:
+            suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
+
         images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
-                          no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None)
+                          no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
 
         if opts.enable_pnginfo:
             image.info = existing_pnginfo
-- 
cgit v1.2.3


From a7a039d53a69f8c32cb889fe322e769b238fec27 Mon Sep 17 00:00:00 2001
From: timntorres <timothynarcisotorres@gmail.com>
Date: Sat, 17 Dec 2022 06:28:51 -0800
Subject: Add option to include upscaler name in filename.

---
 modules/extras.py | 5 +++--
 modules/shared.py | 1 +
 2 files changed, 4 insertions(+), 2 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 9b60e360..074a7c22 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -194,8 +194,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
             basename = ''
 
         # Add upscaler name as a suffix.
-        suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}"
-        if extras_upscaler_2 and extras_upscaler_2_visibility:
+        suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
+        # Add second upscaler if applicable.
+        if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
             suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
 
         images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
diff --git a/modules/shared.py b/modules/shared.py
index dc45fcaa..218894e8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -293,6 +293,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"),
 
     "use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process in extras tab"),
+    "use_upscaler_name_as_suffix": OptionInfo(False, "Add upscaler name to the end of filename in the 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"),
 
-- 
cgit v1.2.3


From 6247f21a637399900643a4915e8a223688e0ed22 Mon Sep 17 00:00:00 2001
From: Philpax <me@philpax.me>
Date: Sat, 24 Dec 2022 22:04:53 +1100
Subject: fix(api): don't save extras output to disk

---
 modules/api/api.py |  6 +++---
 modules/extras.py  | 17 +++++++++--------
 2 files changed, 12 insertions(+), 11 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/api/api.py b/modules/api/api.py
index 3257445d..b43dd16b 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -181,7 +181,7 @@ class Api:
         reqDict['image'] = decode_base64_to_image(reqDict['image'])
 
         with self.queue_lock:
-            result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", **reqDict)
+            result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
 
         return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
 
@@ -197,7 +197,7 @@ class Api:
         reqDict.pop('imageList')
 
         with self.queue_lock:
-            result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", **reqDict)
+            result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", save_output=False, **reqDict)
 
         return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 
@@ -322,7 +322,7 @@ class Api:
 
     def get_artists(self):
         return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists]
-    
+
     def refresh_checkpoints(self):
         shared.refresh_checkpoints()
 
diff --git a/modules/extras.py b/modules/extras.py
index 6fa7d856..68939dea 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -55,7 +55,7 @@ class LruCache(OrderedDict):
 cached_images: LruCache = LruCache(max_size=5)
 
 
-def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool):
+def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True):
     devices.torch_gc()
 
     imageArr = []
@@ -193,14 +193,15 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         else:
             basename = ''
 
-        # Add upscaler name as a suffix.
-        suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
-        # Add second upscaler if applicable.
-        if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
-            suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
+        if save_output:
+            # Add upscaler name as a suffix.
+            suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
+            # Add second upscaler if applicable.
+            if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
+                suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
 
-        images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
-                          no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
+            images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
+                            no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
 
         if opts.enable_pnginfo:
             image.info = existing_pnginfo
-- 
cgit v1.2.3


From 84dd7e8e2495c4fc2997e97f8267aa831eb90d11 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 2 Jan 2023 20:30:02 +0300
Subject: error out with a readable message in chwewckpoint merger for
 incompatible tensor shapes (ie when trying to merge SD1.5 with SD2.0)

---
 modules/extras.py | 2 ++
 modules/ui.py     | 2 +-
 2 files changed, 3 insertions(+), 1 deletion(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 68939dea..5e270250 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -303,6 +303,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                 theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
                 result_is_inpainting_model = True
             else:
+                assert a.shape == b.shape, f'Incompatible shapes for layer {key}: A is {a.shape}, and B is {b.shape}'
+
                 theta_0[key] = theta_func2(a, b, multiplier)
 
             if save_as_half:
diff --git a/modules/ui.py b/modules/ui.py
index 27cd9ddd..67a51888 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1663,7 +1663,7 @@ def create_ui():
                 print("Error loading/saving model file:", file=sys.stderr)
                 print(traceback.format_exc(), file=sys.stderr)
                 modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)]
+                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
             return results
 
         modelmerger_merge.click(
-- 
cgit v1.2.3


From 1d9dc48efda2e8da6d13fc62e65500198a9b041c Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Tue, 3 Jan 2023 10:21:51 -0500
Subject: init job and add info to model merge

---
 modules/extras.py | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 5e270250..7e222313 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -242,6 +242,9 @@ def run_pnginfo(image):
 
 
 def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
+    shared.state.begin()
+    shared.state.job = 'model-merge'
+
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
@@ -263,8 +266,11 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     theta_func1, theta_func2 = theta_funcs[interp_method]
 
     if theta_func1 and not tertiary_model_info:
+        shared.state.textinfo = "Failed: Interpolation method requires a tertiary model."
+        shared.state.end()
         return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
 
+    shared.state.textinfo = f"Loading {secondary_model_info.filename}..."
     print(f"Loading {secondary_model_info.filename}...")
     theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
 
@@ -281,6 +287,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                     theta_1[key] = torch.zeros_like(theta_1[key])
         del theta_2
 
+    shared.state.textinfo = f"Loading {primary_model_info.filename}..."
     print(f"Loading {primary_model_info.filename}...")
     theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
 
@@ -291,6 +298,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
             a = theta_0[key]
             b = theta_1[key]
 
+            shared.state.textinfo = f'Merging layer {key}'
             # this enables merging an inpainting model (A) with another one (B);
             # where normal model would have 4 channels, for latenst space, inpainting model would
             # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
@@ -303,8 +311,6 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                 theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
                 result_is_inpainting_model = True
             else:
-                assert a.shape == b.shape, f'Incompatible shapes for layer {key}: A is {a.shape}, and B is {b.shape}'
-
                 theta_0[key] = theta_func2(a, b, multiplier)
 
             if save_as_half:
@@ -332,6 +338,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
 
     output_modelname = os.path.join(ckpt_dir, filename)
 
+    shared.state.textinfo = f"Saving to {output_modelname}..."
     print(f"Saving to {output_modelname}...")
 
     _, extension = os.path.splitext(output_modelname)
@@ -343,4 +350,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     sd_models.list_models()
 
     print("Checkpoint saved.")
+    shared.state.textinfo = "Checkpoint saved to " + output_modelname
+    shared.state.end()
+
     return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
-- 
cgit v1.2.3


From 192ddc04d6de0d780f73aa5fbaa8c66cd4642e1c Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Tue, 3 Jan 2023 10:34:51 -0500
Subject: add job info to modules

---
 modules/extras.py                              | 17 +++++++++++++----
 modules/hypernetworks/hypernetwork.py          |  1 +
 modules/textual_inversion/preprocess.py        |  1 +
 modules/textual_inversion/textual_inversion.py |  1 +
 4 files changed, 16 insertions(+), 4 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index 7e222313..d665440a 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -58,6 +58,9 @@ cached_images: LruCache = LruCache(max_size=5)
 def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True):
     devices.torch_gc()
 
+    shared.state.begin()
+    shared.state.job = 'extras'
+
     imageArr = []
     # Also keep track of original file names
     imageNameArr = []
@@ -94,6 +97,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
     # Extra operation definitions
 
     def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
+        shared.state.job = 'extras-gfpgan'
         restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
         res = Image.fromarray(restored_img)
 
@@ -104,6 +108,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         return (res, info)
 
     def run_codeformer(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
+        shared.state.job = 'extras-codeformer'
         restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
         res = Image.fromarray(restored_img)
 
@@ -114,6 +119,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         return (res, info)
 
     def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
+        shared.state.job = 'extras-upscale'
         upscaler = shared.sd_upscalers[scaler_index]
         res = upscaler.scaler.upscale(image, resize, upscaler.data_path)
         if mode == 1 and crop:
@@ -180,6 +186,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
     for image, image_name in zip(imageArr, imageNameArr):
         if image is None:
             return outputs, "Please select an input image.", ''
+
+        shared.state.textinfo = f'Processing image {image_name}'
+        
         existing_pnginfo = image.info or {}
 
         image = image.convert("RGB")
@@ -193,6 +202,10 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
         else:
             basename = ''
 
+        if opts.enable_pnginfo: # append info before save
+            image.info = existing_pnginfo
+            image.info["extras"] = info
+
         if save_output:
             # Add upscaler name as a suffix.
             suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
@@ -203,10 +216,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
             images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
                             no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
 
-        if opts.enable_pnginfo:
-            image.info = existing_pnginfo
-            image.info["extras"] = info
-
         if extras_mode != 2 or show_extras_results :
             outputs.append(image)
 
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 109e8078..450fecac 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -417,6 +417,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
     shared.loaded_hypernetwork = Hypernetwork()
     shared.loaded_hypernetwork.load(path)
 
+    shared.state.job = "train-hypernetwork"
     shared.state.textinfo = "Initializing hypernetwork training..."
     shared.state.job_count = steps
 
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 56b9b2eb..feb876c6 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -124,6 +124,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
 
     files = listfiles(src)
 
+    shared.state.job = "preprocess"
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index fd253477..2c1251d6 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -245,6 +245,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
     create_image_every = create_image_every or 0
     validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
 
+    shared.state.job = "train-embedding"
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
 
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