remove all traces from v1 + improve filelist path

.gitignore

@@ -18,5 +18,4 @@
 logs
 env
 venv
-.venv
-rvc/models
+.venv

app.py

@@ -32,8 +32,6 @@
 from core import run_prerequisites_script
 
 run_prerequisites_script(
-    pretraineds_v1_f0=False,
-    pretraineds_v1_nof0=False,
     pretraineds_v2_f0=True,
     pretraineds_v2_nof0=False,
     models=True,

assets/Applio_NoUI.ipynb

@@ -447,7 +447,6 @@
    "outputs": [],
    "source": [
     "# @title Extract Features\n",
-    "rvc_version = \"v2\"  # @param [\"v2\", \"v1\"] {allow-input: false}\n",
     "f0_method = \"rmvpe\"  # @param [\"crepe\", \"crepe-tiny\", \"rmvpe\"] {allow-input: false}\n",
     "hop_length = 128  # @param {type:\"slider\", min:1, max:512, step:0}\n",
     "\n",
@@ -456,7 +455,7 @@
     "embedder_model = \"contentvec\" # @param [\"contentvec\", \"chinese-hubert-base\", \"japanese-hubert-base\", \"korean-hubert-base\", \"custom\"] {allow-input: false}\n",
     "embedder_model_custom = \"\" # @param {type:\"string\"}\n",
     "\n",
-    "!python core.py extract --model_name \"{model_name}\" --rvc_version \"{rvc_version}\" --f0_method \"{f0_method}\" --hop_length \"{hop_length}\" --sample_rate \"{sr}\" --cpu_cores \"{cpu_cores}\" --gpu \"0\" --embedder_model \"{embedder_model}\" --embedder_model_custom \"{embedder_model_custom}\""
+    "!python core.py extract --model_name \"{model_name}\" --f0_method \"{f0_method}\" --hop_length \"{hop_length}\" --sample_rate \"{sr}\" --cpu_cores \"{cpu_cores}\" --gpu \"0\" --embedder_model \"{embedder_model}\" --embedder_model_custom \"{embedder_model_custom}\""
    ]
   },
   {
@@ -636,7 +635,7 @@
     "    if tensorboard == True:\n",
     "        %load_ext tensorboard\n",
     "        %tensorboard --logdir /content/Applio/logs/\n",
-    "    !python core.py train --model_name \"{model_name}\" --rvc_version \"{rvc_version}\" --save_every_epoch \"{save_every_epoch}\" --save_only_latest \"{save_only_latest}\" --save_every_weights \"{save_every_weights}\" --total_epoch \"{total_epoch}\" --sample_rate \"{sr}\" --batch_size \"{batch_size}\" --gpu \"{gpu}\" --pretrained \"{pretrained}\" --custom_pretrained \"{custom_pretrained}\" --g_pretrained_path \"{g_pretrained_path}\" --d_pretrained_path \"{d_pretrained_path}\" --overtraining_detector \"{overtraining_detector}\" --overtraining_threshold \"{overtraining_threshold}\" --cleanup \"{cleanup}\" --cache_data_in_gpu \"{cache_data_in_gpu}\"\n",
+    "    !python core.py train --model_name \"{model_name}\" --save_every_epoch \"{save_every_epoch}\" --save_only_latest \"{save_only_latest}\" --save_every_weights \"{save_every_weights}\" --total_epoch \"{total_epoch}\" --sample_rate \"{sr}\" --batch_size \"{batch_size}\" --gpu \"{gpu}\" --pretrained \"{pretrained}\" --custom_pretrained \"{custom_pretrained}\" --g_pretrained_path \"{g_pretrained_path}\" --d_pretrained_path \"{d_pretrained_path}\" --overtraining_detector \"{overtraining_detector}\" --overtraining_threshold \"{overtraining_threshold}\" --cleanup \"{cleanup}\" --cache_data_in_gpu \"{cache_data_in_gpu}\"\n",
     "\n",
     "\n",
     "server_thread = threading.Thread(target=start_train)\n",
@@ -660,7 +659,7 @@
    "source": [
     "# @title Generate index file\n",
     "index_algorithm = \"Auto\"  # @param [\"Auto\", \"Faiss\", \"KMeans\"] {allow-input: false}\n",
-    "!python core.py index --model_name \"{model_name}\" --rvc_version \"{rvc_version}\" --index_algorithm \"{index_algorithm}\""
+    "!python core.py index --model_name \"{model_name}\" --index_algorithm \"{index_algorithm}\""
    ]
   },
   {
@@ -789,7 +788,6 @@
     "# @markdown ### ➡️ Use the same as you did previously\n",
     "model_name = \"Darwin\"  # @param {type:\"string\"}\n",
     "sample_rate = \"40k\"  # @param [\"32k\", \"40k\", \"48k\"] {allow-input: false}\n",
-    "rvc_version = \"v2\"  # @param [\"v2\", \"v1\"] {allow-input: false}\n",
     "f0_method = \"rmvpe\"  # @param [\"crepe\", \"crepe-tiny\", \"rmvpe\"] {allow-input: false}\n",
     "hop_length = 128  # @param {type:\"slider\", min:1, max:512, step:0}\n",
     "sr = int(sample_rate.rstrip(\"k\")) * 1000"

core.py

@@ -454,7 +454,6 @@ def run_preprocess_script(
 # Extract
 def run_extract_script(
     model_name: str,
-    rvc_version: str,
     f0_method: str,
     hop_length: int,
     cpu_cores: int,
@@ -479,7 +478,6 @@ def run_extract_script(
                 hop_length,
                 cpu_cores,
                 gpu,
-                rvc_version,
                 sample_rate,
                 embedder_model,
                 embedder_model_custom,
@@ -496,7 +494,6 @@ def run_extract_script(
 # Train
 def run_train_script(
     model_name: str,
-    rvc_version: str,
     save_every_epoch: int,
     save_only_latest: bool,
     save_every_weights: bool,
@@ -522,7 +519,7 @@ def run_train_script(
 
         if custom_pretrained == False:
             pg, pd = pretrained_selector(
-                str(rvc_version), str(vocoder), True, int(sample_rate)
+                str(vocoder), True, int(sample_rate)
             )
         else:
             if g_pretrained_path is None or d_pretrained_path is None:
@@ -545,7 +542,6 @@ def run_train_script(
                 total_epoch,
                 pg,
                 pd,
-                rvc_version,
                 gpu,
                 batch_size,
                 sample_rate,
@@ -561,18 +557,17 @@ def run_train_script(
         ),
     ]
     subprocess.run(command)
-    run_index_script(model_name, rvc_version, index_algorithm)
+    run_index_script(model_name, index_algorithm)
     return f"Model {model_name} trained successfully."
 
 
 # Index
-def run_index_script(model_name: str, rvc_version: str, index_algorithm: str):
+def run_index_script(model_name: str, index_algorithm: str):
     index_script_path = os.path.join("rvc", "train", "process", "extract_index.py")
     command = [
         python,
         index_script_path,
         os.path.join(logs_path, model_name),
-        rvc_version,
         index_algorithm,
     ]
 
@@ -607,16 +602,12 @@ def run_download_script(model_link: str):
 
 # Prerequisites
 def run_prerequisites_script(
-    pretraineds_v1_f0: bool,
-    pretraineds_v1_nof0: bool,
     pretraineds_v2_f0: bool,
     pretraineds_v2_nof0: bool,
     models: bool,
     exe: bool,
 ):
     prequisites_download_pipeline(
-        pretraineds_v1_f0,
-        pretraineds_v1_nof0,
         pretraineds_v2_f0,
         pretraineds_v2_nof0,
         models,
@@ -1893,13 +1884,6 @@ def parse_arguments():
     extract_parser.add_argument(
         "--model_name", type=str, help="Name of the model.", required=True
     )
-    extract_parser.add_argument(
-        "--rvc_version",
-        type=str,
-        help="Version of the RVC model ('v1' or 'v2').",
-        choices=["v1", "v2"],
-        default="v2",
-    )
     extract_parser.add_argument(
         "--f0_method",
         type=str,
@@ -1971,13 +1955,6 @@ def parse_arguments():
     train_parser.add_argument(
         "--model_name", type=str, help="Name of the model to be trained.", required=True
     )
-    train_parser.add_argument(
-        "--rvc_version",
-        type=str,
-        help="Version of the RVC model to train ('v1' or 'v2').",
-        choices=["v1", "v2"],
-        default="v2",
-    )
     train_parser.add_argument(
         "--vocoder",
         type=str,
@@ -2113,13 +2090,6 @@ def parse_arguments():
     index_parser.add_argument(
         "--model_name", type=str, help="Name of the model.", required=True
     )
-    index_parser.add_argument(
-        "--rvc_version",
-        type=str,
-        help="Version of the RVC model ('v1' or 'v2').",
-        choices=["v1", "v2"],
-        default="v2",
-    )
     index_parser.add_argument(
         "--index_algorithm",
         type=str,
@@ -2181,27 +2151,13 @@ def parse_arguments():
     prerequisites_parser = subparsers.add_parser(
         "prerequisites", help="Install prerequisites for RVC."
     )
-    prerequisites_parser.add_argument(
-        "--pretraineds_v1_f0",
-        type=lambda x: bool(strtobool(x)),
-        choices=[True, False],
-        default=False,
-        help="Download pretrained models for RVC v1.",
-    )
     prerequisites_parser.add_argument(
         "--pretraineds_v2_f0",
         type=lambda x: bool(strtobool(x)),
         choices=[True, False],
         default=True,
         help="Download pretrained models for RVC v2.",
     )
-    prerequisites_parser.add_argument(
-        "--pretraineds_v1_nof0",
-        type=lambda x: bool(strtobool(x)),
-        choices=[True, False],
-        default=False,
-        help="Download non f0 pretrained models for RVC v1.",
-    )
     prerequisites_parser.add_argument(
         "--pretraineds_v2_nof0",
         type=lambda x: bool(strtobool(x)),
@@ -2412,7 +2368,6 @@ def main():
         elif args.mode == "extract":
             run_extract_script(
                 model_name=args.model_name,
-                rvc_version=args.rvc_version,
                 f0_method=args.f0_method,
                 hop_length=args.hop_length,
                 cpu_cores=args.cpu_cores,
@@ -2425,7 +2380,6 @@ def main():
         elif args.mode == "train":
             run_train_script(
                 model_name=args.model_name,
-                rvc_version=args.rvc_version,
                 save_every_epoch=args.save_every_epoch,
                 save_only_latest=args.save_only_latest,
                 save_every_weights=args.save_every_weights,
@@ -2448,7 +2402,6 @@ def main():
         elif args.mode == "index":
             run_index_script(
                 model_name=args.model_name,
-                rvc_version=args.rvc_version,
                 index_algorithm=args.index_algorithm,
             )
         elif args.mode == "model_information":
@@ -2470,8 +2423,6 @@ def main():
             )
         elif args.mode == "prerequisites":
             run_prerequisites_script(
-                pretraineds_v1_f0=args.pretraineds_v1_f0,
-                pretraineds_v1_nof0=args.pretraineds_v1_nof0,
                 pretraineds_v2_f0=args.pretraineds_v2_f0,
                 pretraineds_v2_nof0=args.pretraineds_v2_nof0,
                 models=args.models,

rvc/configs/config.py

@@ -3,14 +3,10 @@
 import os
 
 version_config_paths = [
-    os.path.join("v1", "32000.json"),
-    os.path.join("v1", "40000.json"),
-    os.path.join("v1", "44100.json"),
-    os.path.join("v1", "48000.json"),
-    os.path.join("v2", "48000.json"),
-    os.path.join("v2", "40000.json"),
-    os.path.join("v2", "44100.json"),
-    os.path.join("v2", "32000.json"),
+    os.path.join("48000.json"),
+    os.path.join("40000.json"),
+    os.path.join("44100.json"),
+    os.path.join("32000.json"),
 ]