- Add new tool to verify LoRA weights produced by the trainer. Can be found under "Dreambooth LoRA/Tools/Verify LoRA

README.md

@@ -114,8 +114,24 @@ Once you have created the LoRA network you can generate images via auto1111 by i
 
 - Re-install python 3.10.x on your system: https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe
 
+### FileNotFoundError
+
+This is usually related to an installation issue. Make sure you do not have python modules installed locally that could conflict with the ones installed in the venv:
+
+1. Open a new powershell terminal and make sure no venv is active.
+2.  Run the following commands
+
+```
+pip freeze > uninstall.txt
+pip uninstall -r uninstall.txt
+```
+
+Then redo the installation instruction within the kohya_ss venv.
+
 ## Change history
 
+* 2023/01/22 (v20.4.1):
+    - Add new tool to verify LoRA weights produced by the trainer. Can be found under "Dreambooth LoRA/Tools/Verify LoRA"
 * 2023/01/22 (v20.4.0):
     - Add support for `network_alpha` under the Training tab and support for `--training_comment` under the Folders tab.
     - Add ``--network_alpha`` option to specify ``alpha`` value to prevent underflows for stable training. Thanks to CCRcmcpe!

library/verify_lora_gui.py

@@ -0,0 +1,91 @@
+import gradio as gr
+from easygui import msgbox
+import subprocess
+import os
+from .common_gui import get_saveasfilename_path, get_any_file_path, get_file_path
+
+folder_symbol = '\U0001f4c2'  # 📂
+refresh_symbol = '\U0001f504'  # 🔄
+save_style_symbol = '\U0001f4be'  # 💾
+document_symbol = '\U0001F4C4'   # 📄
+
+
+def verify_lora(
+    lora_model,
+):
+    # verify for caption_text_input
+    if lora_model == '':
+        msgbox('Invalid model A file')
+        return
+
+    # verify if source model exist
+    if not os.path.isfile(lora_model):
+        msgbox('The provided model A is not a file')
+        return
+
+    run_cmd = f'.\\venv\Scripts\python.exe "networks\check_lora_weights.py"'
+    run_cmd += f' {lora_model}'
+
+    print(run_cmd)
+
+    # Run the command
+    subprocess.run(run_cmd)
+    process = subprocess.Popen(run_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    output, error = process.communicate()
+    
+    return (output.decode(), error.decode())
+
+
+###
+# Gradio UI
+###
+
+
+def gradio_verify_lora_tab():
+    with gr.Tab('Verify LoRA'):
+        gr.Markdown(
+            'This utility can verify a LoRA network to make sure it is properly trained.'
+        )
+        
+        lora_ext = gr.Textbox(value='*.pt *.safetensors', visible=False)
+        lora_ext_name = gr.Textbox(value='LoRA model types', visible=False)
+        
+        with gr.Row():
+            lora_model = gr.Textbox(
+                label='LoRA model',
+                placeholder='Path to the LoRA model to verify',
+                interactive=True,
+            )
+            button_lora_model_file = gr.Button(
+                folder_symbol, elem_id='open_folder_small'
+            )
+            button_lora_model_file.click(
+                get_file_path,
+                inputs=[lora_model, lora_ext, lora_ext_name],
+                outputs=lora_model,
+            )
+            verify_button = gr.Button('Verify', variant="primary")
+
+        lora_model_verif_output = gr.Textbox(
+            label='Output',
+            placeholder='Verification output',
+            interactive=False,
+            lines=1,
+            max_lines=10,
+        )
+        
+        lora_model_verif_error = gr.Textbox(
+            label='Error',
+            placeholder='Verification error',
+            interactive=False,
+            lines=1,
+            max_lines=10,
+        )
+
+        verify_button.click(
+            verify_lora,
+            inputs=[
+                lora_model,
+            ],
+            outputs=[lora_model_verif_output, lora_model_verif_error]
+        )

lora_gui.py

@@ -31,6 +31,7 @@ from library.dreambooth_folder_creation_gui import (
 from library.dataset_balancing_gui import gradio_dataset_balancing_tab
 from library.utilities import utilities_tab
 from library.merge_lora_gui import gradio_merge_lora_tab
+from library.verify_lora_gui import gradio_verify_lora_tab
 from easygui import msgbox
 
 folder_symbol = '\U0001f4c2'  # 📂
@@ -675,6 +676,8 @@ def lora_tab(
         )
         gradio_dataset_balancing_tab()
         gradio_merge_lora_tab()
+        gradio_verify_lora_tab()
+        
 
     button_run = gr.Button('Train model')
 

setup.py

@@ -1,3 +1,3 @@
 from setuptools import setup, find_packages
  
-setup(name = "library", version="1.0.1", packages = find_packages())
+setup(name = "library", version="1.0.2", packages = find_packages())