refactor: use central flag for LoRA count

modules/async_worker.py

@@ -44,7 +44,7 @@ def worker():
     from modules.util import remove_empty_str, HWC3, resize_image, \
         get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, calculate_sha256
     from modules.upscaler import perform_upscale
-    from modules.flags import Performance, MetadataScheme
+    from modules.flags import Performance, MetadataScheme, lora_count
 
     try:
         async_gradio_app = shared.gradio_root
@@ -134,7 +134,7 @@ def worker():
         base_model_name = args.pop()
         refiner_model_name = args.pop()
         refiner_switch = args.pop()
-        loras = [[str(args.pop()), float(args.pop())] for _ in range(5)]
+        loras = [[str(args.pop()), float(args.pop())] for _ in range(lora_count)]
         input_image_checkbox = args.pop()
         current_tab = args.pop()
         uov_method = args.pop()

modules/config.py

@@ -8,7 +8,7 @@ import modules.sdxl_styles
 
 from modules.model_loader import load_file_from_url
 from modules.util import get_files_from_folder
-from modules.flags import Performance, MetadataScheme
+from modules.flags import Performance, MetadataScheme, lora_count
 
 config_path = os.path.abspath("./config.txt")
 config_example_path = os.path.abspath("config_modification_tutorial.txt")
@@ -333,7 +333,7 @@ metadata_created_by = get_config_item_or_set_default(
 
 example_inpaint_prompts = [[x] for x in example_inpaint_prompts]
 
-config_dict["default_loras"] = default_loras = default_loras[:5] + [['None', 1.0] for _ in range(5 - len(default_loras))]
+config_dict["default_loras"] = default_loras = default_loras[:lora_count] + [['None', 1.0] for _ in range(lora_count - len(default_loras))]
 
 possible_preset_keys = [
     "default_model",

modules/flags.py

@@ -55,6 +55,8 @@ metadata_scheme = [
     ('A1111 (plain text)', MetadataScheme.A1111.value),
 ]
 
+lora_count = 5
+lora_count_with_lcm = lora_count + 1
 
 class Steps(Enum):
     QUALITY = 60

modules/meta_parser.py

@@ -3,6 +3,7 @@ import json
 import gradio as gr
 
 import modules.config
+from modules.flags import lora_count_with_lcm
 
 
 def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool):
@@ -35,7 +36,7 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool):
 
     results.append(gr.update(visible=False))
 
-    for i in range(1, 6):
+    for i in range(1, lora_count_with_lcm):
         try:
             n, w = loaded_parameter_dict.get(f'LoRA {i}').split(' : ')
             w = float(w)

modules/metadata.py

@@ -7,7 +7,7 @@ import modules.config
 import fooocus_version
 # import advanced_parameters
 from modules.util import quote, unquote, extract_styles_from_prompt, is_json
-from modules.flags import MetadataScheme, Performance, Steps
+from modules.flags import MetadataScheme, Performance, Steps, lora_count_with_lcm
 
 re_param_code = r'\s*(\w[\w \-/]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'
 re_param = re.compile(re_param_code)
@@ -106,7 +106,7 @@ class A1111MetadataParser(MetadataParser):
         width, heigth = eval(data['resolution'])
 
         lora_hashes = []
-        for index in range(5):
+        for index in range(lora_count_with_lcm):
             key = f'lora_name_{index + 1}'
             if key in data:
                 name = data[f'lora_name_{index + 1}']

webui.py

@@ -502,7 +502,7 @@ with shared.gradio_root:
                     modules.config.update_all_model_names()
                     results = []
                     results += [gr.update(choices=modules.config.model_filenames), gr.update(choices=['None'] + modules.config.model_filenames)]
-                    for i in range(5):
+                    for i in range(flags.lora_count):
                         results += [gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
                     return results