Add preprocess_all.py and optimize cli settings

gen_yaml.py

@@ -3,22 +3,20 @@ import shutil
 import yaml
 import argparse
 
-parser = argparse.ArgumentParser(description="config.ymlの生成。あらかじめ前準備をしたデータをバッチファイルなどで連続で学習する時にtrain_ms.pyより前に使用する。")
-# そうしないと最後の前準備したデータで学習してしまう
-parser.add_argument(
-    "--model_name",
-    type=str,
-    help="Model name",
-    required=True
+parser = argparse.ArgumentParser(
+    description="config.ymlの生成。あらかじめ前準備をしたデータをバッチファイルなどで連続で学習する時にtrain_ms.pyより前に使用する。"
 )
+# そうしないと最後の前準備したデータで学習してしまう
+parser.add_argument("--model_name", type=str, help="Model name", required=True)
 parser.add_argument(
     "--dataset_path",
     type=str,
     help="Dataset path(example: Data\\your_model_name)",
-    required=True
+    required=True,
 )
 args = parser.parse_args()
 
+
 def gen_yaml(model_name, dataset_path):
     if not os.path.exists("config.yml"):
         shutil.copy(src="default_config.yml", dst="config.yml")
@@ -29,6 +27,6 @@ def gen_yaml(model_name, dataset_path):
     with open("config.yml", "w", encoding="utf-8") as f:
         yaml.dump(yml_data, f, allow_unicode=True)
 
+
 if __name__ == "__main__":
     gen_yaml(args.model_name, args.dataset_path)
-

initialize.py

@@ -2,6 +2,7 @@ import argparse
 import json
 from pathlib import Path
 
+import yaml
 from huggingface_hub import hf_hub_download
 
 from common.log import logger
@@ -90,9 +91,21 @@ def download_jvnv_models():
             )
 
 
-if __name__ == "__main__":
+def main():
     parser = argparse.ArgumentParser()
     parser.add_argument("--skip_jvnv", action="store_true")
+    parser.add_argument(
+        "--dataset_root",
+        type=str,
+        help="Dataset root path (default: Data)",
+        default=None,
+    )
+    parser.add_argument(
+        "--assets_root",
+        type=str,
+        help="Assets root path (default: model_assets)",
+        default=None,
+    )
     args = parser.parse_args()
 
     download_bert_models()
@@ -105,3 +118,21 @@ if __name__ == "__main__":
 
     if not args.skip_jvnv:
         download_jvnv_models()
+
+    if args.dataset_root is None and args.assets_root is None:
+        return
+
+    # Change default paths if necessary
+    paths_yml = Path("configs/paths.yml")
+    with open(paths_yml, "r", encoding="utf-8") as f:
+        yml_data = yaml.safe_load(f)
+    if args.assets_root is not None:
+        yml_data["assets_root"] = args.assets_root
+    if args.dataset_root is not None:
+        yml_data["dataset_root"] = args.dataset_root
+    with open(paths_yml, "w", encoding="utf-8") as f:
+        yaml.dump(yml_data, f, allow_unicode=True)
+
+
+if __name__ == "__main__":
+    main()

preprocess_all.py

@@ -0,0 +1,96 @@
+import argparse
+from webui_train import preprocess_all
+from multiprocessing import cpu_count
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_name", "-m", type=str, help="Model name", required=True
+    )
+    parser.add_argument("--batch_size", "-b", type=int, help="Batch size", default=2)
+    parser.add_argument("--epochs", "-e", type=int, help="Epochs", default=100)
+    parser.add_argument(
+        "--save_every_steps",
+        "-s",
+        type=int,
+        help="Save every steps",
+        default=1000,
+    )
+    parser.add_argument(
+        "--num_processes",
+        type=int,
+        help="Number of processes",
+        default=cpu_count() // 2,
+    )
+    parser.add_argument(
+        "--normalize",
+        action="store_true",
+        help="Loudness normalize audio",
+    )
+    parser.add_argument(
+        "--trim",
+        action="store_true",
+        help="Trim silence",
+    )
+    parser.add_argument(
+        "--freeze_EN_bert",
+        action="store_true",
+        help="Freeze English BERT",
+    )
+    parser.add_argument(
+        "--freeze_JP_bert",
+        action="store_true",
+        help="Freeze Japanese BERT",
+    )
+    parser.add_argument(
+        "--freeze_ZH_bert",
+        action="store_true",
+        help="Freeze Chinese BERT",
+    )
+    parser.add_argument(
+        "--freeze_style",
+        action="store_true",
+        help="Freeze style vector",
+    )
+    parser.add_argument(
+        "--use_jp_extra",
+        action="store_true",
+        help="Use JP-Extra pretrained model",
+    )
+    parser.add_argument(
+        "--val_per_lang",
+        type=int,
+        help="Validation per language",
+        default=0,
+    )
+    parser.add_argument(
+        "--log_interval",
+        type=int,
+        help="Log interval",
+        default=200,
+    )
+    parser.add_argument(
+        "--skip_invalid",
+        action="store_true",
+        help="Skip invalid",
+    )
+
+    args = parser.parse_args()
+
+    preprocess_all(
+        model_name=args.model_name,
+        batch_size=args.batch_size,
+        epochs=args.epochs,
+        save_every_steps=args.save_every_steps,
+        num_processes=args.num_processes,
+        normalize=args.normalize,
+        trim=args.trim,
+        freeze_EN_bert=args.freeze_EN_bert,
+        freeze_JP_bert=args.freeze_JP_bert,
+        freeze_ZH_bert=args.freeze_ZH_bert,
+        freeze_style=args.freeze_style,
+        use_jp_extra=args.use_jp_extra,
+        val_per_lang=args.val_per_lang,
+        log_interval=args.log_interval,
+        skip_invalid=args.skip_invalid,
+    )