refactor config parse, feature to output config

fine_tune.py

@@ -408,24 +408,6 @@ if __name__ == "__main__":
     parser.add_argument("--train_text_encoder", action="store_true", help="train text encoder / text encoderも学習する")
 
     args = parser.parse_args()
-
+    args = train_util.read_config_from_file(args, parser)
-    if args.config_file:
-        config_path = args.config_file + ".toml" if not args.config_file.endswith(".toml") else args.config_file
-        if os.path.exists(config_path):
-            print(f"Loading settings from {config_path}...")
-            with open(config_path, "r") as f:
-                config_dict = toml.load(f)
-
-            ignore_nesting_dict = {}
-            for section_name, section_dict in config_dict.items():
-                for key, value in section_dict.items():
-                    ignore_nesting_dict[key] = value
-
-            config_args = argparse.Namespace(**ignore_nesting_dict)
-            args = parser.parse_args(namespace=config_args)
-            args.config_file = args.config_file.split(".")[0]
-            print(args.config_file)
-        else:
-            print(f"{config_path} not found.")
 
     train(args)

library/train_util.py

@@ -3,6 +3,7 @@
 import argparse
 import importlib
 import json
+import pathlib
 import re
 import shutil
 import time
@@ -23,6 +24,7 @@ import random
 import hashlib
 import subprocess
 from io import BytesIO
+import toml
 
 from tqdm import tqdm
 import torch
@@ -1889,7 +1891,15 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
         help=f"sampler (scheduler) type for sample images / サンプル出力時のサンプラー（スケジューラ）の種類",
     )
 
-    parser.add_argument("--config_file", type=str, default=None, help="using .toml instead of args to pass hyperparameter")
+    parser.add_argument(
+        "--config_file",
+        type=str,
+        default=None,
+        help="using .toml instead of args to pass hyperparameter / ハイパーパラメータを引数ではなく.tomlファイルで渡す",
+    )
+    parser.add_argument(
+        "--output_config", action="store_true", help="output command line args to given .toml file / 引数を.tomlファイルに出力する"
+    )
 
     if support_dreambooth:
         # DreamBooth training
@@ -2016,6 +2026,66 @@ def add_sd_saving_arguments(parser: argparse.ArgumentParser):
     )
 
 
+def read_config_from_file(args: argparse.Namespace, parser: argparse.ArgumentParser):
+    if not args.config_file:
+        return args
+
+    config_path = args.config_file + ".toml" if not args.config_file.endswith(".toml") else args.config_file
+
+    if args.output_config:
+        # check if config file exists
+        if os.path.exists(config_path):
+            print(f"Config file already exists. Aborting... / 出力先の設定ファイルが既に存在します: {config_path}")
+            exit(1)
+
+        # convert args to dictionary
+        args_dict = vars(args)
+
+        # remove unnecessary keys
+        for key in ["config_file", "output_config"]:
+            if key in args_dict:
+                del args_dict[key]
+
+        # convert Path to str in dictionary
+        for key, value in args_dict.items():
+            if isinstance(value, pathlib.Path):
+                args_dict[key] = str(value)
+
+        # convert to toml and output to file
+        with open(config_path, "w") as f:
+            toml.dump(args_dict, f)
+
+        print(f"Saved config file / 設定ファイルを保存しました: {config_path}")
+        exit(0)
+
+    if not os.path.exists(config_path):
+        print(f"{config_path} not found.")
+        exit(1)
+
+    print(f"Loading settings from {config_path}...")
+    with open(config_path, "r") as f:
+        config_dict = toml.load(f)
+
+    # combine all sections into one
+    ignore_nesting_dict = {}
+    for section_name, section_dict in config_dict.items():
+        # if value is not dict, save key and value as is
+        if not isinstance(section_dict, dict):
+            ignore_nesting_dict[section_name] = section_dict
+            continue
+
+        # if value is dict, save all key and value into one dict
+        for key, value in section_dict.items():
+            ignore_nesting_dict[key] = value
+    
+    config_args = argparse.Namespace(**ignore_nesting_dict)
+    args = parser.parse_args(namespace=config_args)
+    args.config_file = os.path.splitext(args.config_file)[0]
+    print(args.config_file)
+
+    return args
+
+
 # endregion
 
 # region utils

train_db.py

@@ -411,24 +411,6 @@ if __name__ == "__main__":
     )
 
     args = parser.parse_args()
-
+    args = train_util.read_config_from_file(args, parser)
-    if args.config_file:
-        config_path = args.config_file + ".toml" if not args.config_file.endswith(".toml") else args.config_file
-        if os.path.exists(config_path):
-            print(f"Loading settings from {config_path}...")
-            with open(config_path, "r") as f:
-                config_dict = toml.load(f)
-
-            ignore_nesting_dict = {}
-            for section_name, section_dict in config_dict.items():
-                for key, value in section_dict.items():
-                    ignore_nesting_dict[key] = value
-
-            config_args = argparse.Namespace(**ignore_nesting_dict)
-            args = parser.parse_args(namespace=config_args)
-            args.config_file = args.config_file.split(".")[0]
-            print(args.config_file)
-        else:
-            print(f"{config_path} not found.")
 
     train(args)

train_network.py

@@ -695,24 +695,6 @@ if __name__ == "__main__":
     )
 
     args = parser.parse_args()
-
+    args = train_util.read_config_from_file(args, parser)
-    if args.config_file:
-        config_path = args.config_file + ".toml" if not args.config_file.endswith(".toml") else args.config_file
-        if os.path.exists(config_path):
-            print(f"Loading settings from {config_path}...")
-            with open(config_path, "r") as f:
-                config_dict = toml.load(f)
-
-            ignore_nesting_dict = {}
-            for section_name, section_dict in config_dict.items():
-                for key, value in section_dict.items():
-                    ignore_nesting_dict[key] = value
-
-            config_args = argparse.Namespace(**ignore_nesting_dict)
-            args = parser.parse_args(namespace=config_args)
-            args.config_file = args.config_file.split(".")[0]
-            print(args.config_file)
-        else:
-            print(f"{config_path} not found.")
 
     train(args)

train_textual_inversion.py

@@ -573,24 +573,6 @@ if __name__ == "__main__":
     )
 
     args = parser.parse_args()
-
+    args = train_util.read_config_from_file(args, parser)
-    if args.config_file:
-        config_path = args.config_file + ".toml" if not args.config_file.endswith(".toml") else args.config_file
-        if os.path.exists(config_path):
-            print(f"Loading settings from {config_path}...")
-            with open(config_path, "r") as f:
-                config_dict = toml.load(f)
-
-            ignore_nesting_dict = {}
-            for section_name, section_dict in config_dict.items():
-                for key, value in section_dict.items():
-                    ignore_nesting_dict[key] = value
-
-            config_args = argparse.Namespace(**ignore_nesting_dict)
-            args = parser.parse_args(namespace=config_args)
-            args.config_file = args.config_file.split(".")[0]
-            print(args.config_file)
-        else:
-            print(f"{config_path} not found.")
 
     train(args)