Merge pull request #317 from bmaltais/dev

v21.1.5

README.md

@@ -176,6 +176,11 @@ This will store your a backup file with your current locally installed pip packa
 
 ## Change History
 
+* 2023/03/05 (v21.1.5):
+    - Add replace underscore with space option to WD14 captioning. Thanks @sALTaccount!
+    - Improve how custom preset is set and handles.
+    - Add support for `--listen` argument. This allow gradio to listen for connections from other devices on the network (or internet). For example: `gui.ps1 --listen "0.0.0.0"` will allow anyone to connect to the gradio webui.
+    - Updated `Resize LoRA` tab to support LoCon resizing. Added new resize
 * 2023/03/05 (v21.1.4):
     - Removing legacy and confusing use 8bit adam chackbox. It is now configured using the Optimiser drop down list. It will be set properly based on legacy config files.
 * 2023/03/04 (v21.1.3):

finetune/tag_images_by_wd14_tagger.py

@@ -125,7 +125,7 @@ def main(args):
       tag_text = ""
       for i, p in enumerate(prob[4:]):                # numpyとか使うのが良いけど、まあそれほど数も多くないのでループで
         if p >= args.thresh and i < len(tags):
-          tag_text += ", " + tags[i]
+          tag_text += ", " + (tags[i].replace("_", " ") if args.replace_underscores else tags[i])
 
       if len(tag_text) > 0:
         tag_text = tag_text[2:]                   # 最初の ", " を消す
@@ -190,6 +190,7 @@ if __name__ == '__main__':
                       help="extension of caption file (for backward compatibility) / 出力されるキャプションファイルの拡張子（スペルミスしていたのを残してあります）")
   parser.add_argument("--caption_extension", type=str, default=".txt", help="extension of caption file / 出力されるキャプションファイルの拡張子")
   parser.add_argument("--debug", action="store_true", help="debug mode")
+  parser.add_argument("--replace_underscores", action="store_true", help="replace underscores in tags with spaces / タグのアンダースコアをスペースに置き換える")
 
   args = parser.parse_args()
 

kohya_gui.py

@@ -52,6 +52,9 @@ def UI(**kwargs):
     server_port = kwargs.get('server_port', 0)
     inbrowser = kwargs.get('inbrowser', False)
     share = kwargs.get('share', False)
+    server_name = kwargs.get('listen')
+    
+    launch_kwargs['server_name'] = server_name
     if username and password:
         launch_kwargs['auth'] = (username, password)
     if server_port > 0:
@@ -66,6 +69,9 @@ def UI(**kwargs):
 if __name__ == '__main__':
     # torch.cuda.set_per_process_memory_fraction(0.48)
     parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--listen', type=str, default='127.0.0.1', help='IP to listen on for connections to Gradio'
+    )
     parser.add_argument(
         '--username', type=str, default='', help='Username for authentication'
     )
@@ -93,4 +99,5 @@ if __name__ == '__main__':
         inbrowser=args.inbrowser,
         server_port=args.server_port,
         share=args.share,
+        listen=args.listen,
     )

library/common_gui.py

@@ -9,18 +9,47 @@ refresh_symbol = '\U0001f504'  # 🔄
 save_style_symbol = '\U0001f4be'  # 💾
 document_symbol = '\U0001F4C4'   # 📄
 
+# define a list of substrings to search for v2 base models
+V2_BASE_MODELS = [
+    'stabilityai/stable-diffusion-2-1-base',
+    'stabilityai/stable-diffusion-2-base',
+]
+
+# define a list of substrings to search for v_parameterization models
+V_PARAMETERIZATION_MODELS = [
+    'stabilityai/stable-diffusion-2-1',
+    'stabilityai/stable-diffusion-2',
+]
+
+# define a list of substrings to v1.x models
+V1_MODELS = [
+    'CompVis/stable-diffusion-v1-4',
+    'runwayml/stable-diffusion-v1-5',
+]
+
+# define a list of substrings to search for
+ALL_PRESET_MODELS = V2_BASE_MODELS + V_PARAMETERIZATION_MODELS + V1_MODELS
+
 
 def update_my_data(my_data):
     if my_data.get('use_8bit_adam', False) == True:
         my_data['optimizer'] = 'AdamW8bit'
         # my_data['use_8bit_adam'] = False
-        
+
-    if my_data.get('optimizer', 'missing') == 'missing' and my_data.get('use_8bit_adam', False) == False:
+    if (
+        my_data.get('optimizer', 'missing') == 'missing'
+        and my_data.get('use_8bit_adam', False) == False
+    ):
         my_data['optimizer'] = 'AdamW'
 
     if my_data.get('model_list', 'custom') == []:
         print('Old config with empty model list. Setting to custom...')
         my_data['model_list'] = 'custom'
+
+    # If Pretrained model name or path is not one of the preset models then set the preset_model to custom
+    if not my_data.get('pretrained_model_name_or_path', '') in ALL_PRESET_MODELS:
+        my_data['model_list'] = 'custom'
+
     return my_data
 
 
@@ -282,63 +311,76 @@ def save_inference_file(output_dir, v2, v_parameterization, output_name):
 def set_pretrained_model_name_or_path_input(
     model_list, pretrained_model_name_or_path, v2, v_parameterization
 ):
-    # define a list of substrings to search for
-    substrings_v2 = [
-        'stabilityai/stable-diffusion-2-1-base',
-        'stabilityai/stable-diffusion-2-base',
-    ]
-
     # check if $v2 and $v_parameterization are empty and if $pretrained_model_name_or_path contains any of the substrings in the v2 list
-    if str(model_list) in substrings_v2:
+    if str(model_list) in V2_BASE_MODELS:
         print('SD v2 model detected. Setting --v2 parameter')
         v2 = True
         v_parameterization = False
-
+        pretrained_model_name_or_path = str(model_list)
-        return model_list, v2, v_parameterization
-
-    # define a list of substrings to search for v-objective
-    substrings_v_parameterization = [
-        'stabilityai/stable-diffusion-2-1',
-        'stabilityai/stable-diffusion-2',
-    ]
 
     # check if $v2 and $v_parameterization are empty and if $pretrained_model_name_or_path contains any of the substrings in the v_parameterization list
-    if str(model_list) in substrings_v_parameterization:
+    if str(model_list) in V_PARAMETERIZATION_MODELS:
         print(
             'SD v2 v_parameterization detected. Setting --v2 parameter and --v_parameterization'
         )
         v2 = True
         v_parameterization = True
+        pretrained_model_name_or_path = str(model_list)
 
-        return model_list, v2, v_parameterization
+    if str(model_list) in V1_MODELS:
-
-    # define a list of substrings to v1.x
-    substrings_v1_model = [
-        'CompVis/stable-diffusion-v1-4',
-        'runwayml/stable-diffusion-v1-5',
-    ]
-
-    if str(model_list) in substrings_v1_model:
         v2 = False
         v_parameterization = False
-
+        pretrained_model_name_or_path = str(model_list)
-        return model_list, v2, v_parameterization
 
     if model_list == 'custom':
         if (
-            str(pretrained_model_name_or_path) in substrings_v1_model
+            str(pretrained_model_name_or_path) in V1_MODELS
-            or str(pretrained_model_name_or_path) in substrings_v2
+            or str(pretrained_model_name_or_path) in V2_BASE_MODELS
             or str(pretrained_model_name_or_path)
-            in substrings_v_parameterization
+            in V_PARAMETERIZATION_MODELS
         ):
             pretrained_model_name_or_path = ''
             v2 = False
             v_parameterization = False
-        return pretrained_model_name_or_path, v2, v_parameterization
+    return model_list, pretrained_model_name_or_path, v2, v_parameterization
 
-    ###
+def set_v2_checkbox(
-    ### Gradio common GUI section
+    model_list, v2, v_parameterization
-    ###
+):
+    # check if $v2 and $v_parameterization are empty and if $pretrained_model_name_or_path contains any of the substrings in the v2 list
+    if str(model_list) in V2_BASE_MODELS:
+        v2 = True
+        v_parameterization = False
+
+    # check if $v2 and $v_parameterization are empty and if $pretrained_model_name_or_path contains any of the substrings in the v_parameterization list
+    if str(model_list) in V_PARAMETERIZATION_MODELS:
+        v2 = True
+        v_parameterization = True
+
+    if str(model_list) in V1_MODELS:
+        v2 = False
+        v_parameterization = False
+
+    return v2, v_parameterization
+
+def set_model_list(
+    model_list,
+    pretrained_model_name_or_path,
+    v2,
+    v_parameterization,
+):
+
+    if not pretrained_model_name_or_path in ALL_PRESET_MODELS:
+        model_list = 'custom'
+    else:
+        model_list = pretrained_model_name_or_path
+        
+    return model_list, v2, v_parameterization
+
+
+###
+### Gradio common GUI section
+###
 
 
 def gradio_config():
@@ -362,6 +404,15 @@ def gradio_config():
     )
 
 
+def get_pretrained_model_name_or_path_file(
+    model_list, pretrained_model_name_or_path
+):
+    pretrained_model_name_or_path = get_any_file_path(
+        pretrained_model_name_or_path
+    )
+    set_model_list(model_list, pretrained_model_name_or_path)
+
+
 def gradio_source_model():
     with gr.Tab('Source model'):
         # Define the input elements
@@ -419,6 +470,8 @@ def gradio_source_model():
             v_parameterization = gr.Checkbox(
                 label='v_parameterization', value=False
             )
+            v2.change(set_v2_checkbox, inputs=[model_list, v2, v_parameterization], outputs=[v2, v_parameterization],show_progress=False)
+            v_parameterization.change(set_v2_checkbox, inputs=[model_list, v2, v_parameterization], outputs=[v2, v_parameterization],show_progress=False)
         model_list.change(
             set_pretrained_model_name_or_path_input,
             inputs=[
@@ -428,10 +481,28 @@ def gradio_source_model():
                 v_parameterization,
             ],
             outputs=[
+                model_list,
                 pretrained_model_name_or_path,
                 v2,
                 v_parameterization,
             ],
+            show_progress=False,
+        )
+        # Update the model list and parameters when user click outside the button or field
+        pretrained_model_name_or_path.change(
+            set_model_list,
+            inputs=[
+                model_list,
+                pretrained_model_name_or_path,
+                v2,
+                v_parameterization,
+            ],
+            outputs=[
+                model_list,
+                v2,
+                v_parameterization,
+            ],
+            show_progress=False,
         )
     return (
         pretrained_model_name_or_path,

library/resize_lora_gui.py

@@ -17,6 +17,9 @@ def resize_lora(
     save_to,
     save_precision,
     device,
+    dynamic_method,
+    dynamic_param,
+    verbose,
 ):
     # Check for caption_text_input
     if model == '':
@@ -27,16 +30,35 @@ def resize_lora(
     if not os.path.isfile(model):
         msgbox('The provided model is not a file')
         return
+    
+    if dynamic_method == 'sv_ratio':
+        if float(dynamic_param) < 2:
+            msgbox(f'Dynamic parameter for {dynamic_method} need to be 2 or greater...')
+            return
+        
+    if dynamic_method == 'sv_fro' or dynamic_method == 'sv_cumulative':
+        if float(dynamic_param) < 0 or float(dynamic_param) > 1:
+            msgbox(f'Dynamic parameter for {dynamic_method} need to be between 0 and 1...')
+            return
+
+    # Check if save_to end with one of the defines extension. If not add .safetensors.
+    if not save_to.endswith(('.pt', '.safetensors')):
+        save_to += '.safetensors'
 
     if device == '':
         device = 'cuda'
 
-    run_cmd = f'{PYTHON} "{os.path.join("networks","resize_lora.py")}"'
+    run_cmd = f'{PYTHON} "{os.path.join("tools","resize_lora.py")}"'
     run_cmd += f' --save_precision {save_precision}'
     run_cmd += f' --save_to {save_to}'
     run_cmd += f' --model {model}'
     run_cmd += f' --new_rank {new_rank}'
     run_cmd += f' --device {device}'
+    if not dynamic_method == 'None':
+        run_cmd += f' --dynamic_method {dynamic_method}'
+        run_cmd += f' --dynamic_param {dynamic_param}'
+    if verbose:
+        run_cmd += f' --verbose'
 
     print(run_cmd)
 
@@ -56,7 +78,7 @@ def gradio_resize_lora_tab():
     with gr.Tab('Resize LoRA'):
         gr.Markdown('This utility can resize a LoRA.')
 
-        lora_ext = gr.Textbox(value='*.pt *.safetensors', visible=False)
+        lora_ext = gr.Textbox(value='*.safetensors *.pt', visible=False)
         lora_ext_name = gr.Textbox(value='LoRA model types', visible=False)
 
         with gr.Row():
@@ -84,6 +106,27 @@ def gradio_resize_lora_tab():
                 interactive=True,
             )
 
+        with gr.Row():
+            dynamic_method = gr.Dropdown(
+                choices=['None',
+                         'sv_ratio',
+                         'sv_fro',
+                         'sv_cumulative'
+                         ],
+                value='sv_fro',
+                label='Dynamic method',
+                interactive=True
+            )
+            dynamic_param = gr.Textbox(
+                label='Dynamic parameter',
+                value='0.9',
+                interactive=True,
+                placeholder='Value for the dynamic method selected.'
+            )
+            verbose = gr.Checkbox(
+                label='Verbose',
+                value=False
+            )
         with gr.Row():
             save_to = gr.Textbox(
                 label='Save to',
@@ -109,6 +152,7 @@ def gradio_resize_lora_tab():
                 label='Device',
                 placeholder='{Optional) device to use, cuda for GPU. Default: cuda',
                 interactive=True,
+                value='cuda',
             )
 
         convert_button = gr.Button('Resize model')
@@ -121,6 +165,9 @@ def gradio_resize_lora_tab():
                 save_to,
                 save_precision,
                 device,
+                dynamic_method,
+                dynamic_param,
+                verbose,
             ],
             show_progress=False,
         )

library/wd14_caption_gui.py

@@ -5,7 +5,7 @@ from .common_gui import get_folder_path
 import os
 
 
-def caption_images(train_data_dir, caption_extension, batch_size, thresh):
+def caption_images(train_data_dir, caption_extension, batch_size, thresh, replace_underscores):
     # Check for caption_text_input
     # if caption_text_input == "":
     #     msgbox("Caption text is missing...")
@@ -24,6 +24,7 @@ def caption_images(train_data_dir, caption_extension, batch_size, thresh):
     run_cmd = f'accelerate launch "./finetune/tag_images_by_wd14_tagger.py"'
     run_cmd += f' --batch_size="{int(batch_size)}"'
     run_cmd += f' --thresh="{thresh}"'
+    run_cmd += f' --replace_underscores' if replace_underscores else ''
     if caption_extension != '':
         run_cmd += f' --caption_extension="{caption_extension}"'
     run_cmd += f' "{train_data_dir}"'
@@ -75,11 +76,17 @@ def gradio_wd14_caption_gui_tab():
             batch_size = gr.Number(
                 value=1, label='Batch size', interactive=True
             )
+            
+            replace_underscores = gr.Checkbox(
+                label='Replace underscores in filenames with spaces',
+                value=False,
+                interactive=True,
+            )
 
         caption_button = gr.Button('Caption images')
 
         caption_button.click(
             caption_images,
-            inputs=[train_data_dir, caption_extension, batch_size, thresh],
+            inputs=[train_data_dir, caption_extension, batch_size, thresh, replace_underscores],
             show_progress=False,
         )