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import argparse
import json
import shutil
from pathlib import Path
import yaml
from huggingface_hub import hf_hub_download
from style_bert_vits2.logging import logger
def download_bert_models():
with open("bert/bert_models.json", encoding="utf-8") as fp:
models = json.load(fp)
for k, v in models.items():
local_path = Path("bert").joinpath(k)
for file in v["files"]:
if not Path(local_path).joinpath(file).exists():
logger.info(f"Downloading {k} {file}")
hf_hub_download(v["repo_id"], file, local_dir=local_path)
def download_slm_model():
local_path = Path("slm/wavlm-base-plus/")
file = "pytorch_model.bin"
if not Path(local_path).joinpath(file).exists():
logger.info(f"Downloading wavlm-base-plus {file}")
hf_hub_download("microsoft/wavlm-base-plus", file, local_dir=local_path)
def download_pretrained_models():
files = ["G_0.safetensors", "D_0.safetensors", "DUR_0.safetensors"]
local_path = Path("pretrained")
for file in files:
if not Path(local_path).joinpath(file).exists():
logger.info(f"Downloading pretrained {file}")
hf_hub_download(
"litagin/Style-Bert-VITS2-1.0-base", file, local_dir=local_path
)
def download_jp_extra_pretrained_models():
files = ["G_0.safetensors", "D_0.safetensors", "WD_0.safetensors"]
local_path = Path("pretrained_jp_extra")
for file in files:
if not Path(local_path).joinpath(file).exists():
logger.info(f"Downloading JP-Extra pretrained {file}")
hf_hub_download(
"litagin/Style-Bert-VITS2-2.0-base-JP-Extra", file, local_dir=local_path
)
def download_default_models():
files = [
"jvnv-F1-jp/config.json",
"jvnv-F1-jp/jvnv-F1-jp_e160_s14000.safetensors",
"jvnv-F1-jp/style_vectors.npy",
"jvnv-F2-jp/config.json",
"jvnv-F2-jp/jvnv-F2_e166_s20000.safetensors",
"jvnv-F2-jp/style_vectors.npy",
"jvnv-M1-jp/config.json",
"jvnv-M1-jp/jvnv-M1-jp_e158_s14000.safetensors",
"jvnv-M1-jp/style_vectors.npy",
"jvnv-M2-jp/config.json",
"jvnv-M2-jp/jvnv-M2-jp_e159_s17000.safetensors",
"jvnv-M2-jp/style_vectors.npy",
]
for file in files:
if not Path(f"model_assets/{file}").exists():
logger.info(f"Downloading {file}")
hf_hub_download(
"litagin/style_bert_vits2_jvnv",
file,
local_dir="model_assets",
)
additional_files = {
"litagin/sbv2_koharune_ami": [
"koharune-ami/config.json",
"koharune-ami/style_vectors.npy",
"koharune-ami/koharune-ami.safetensors",
],
"litagin/sbv2_amitaro": [
"amitaro/config.json",
"amitaro/style_vectors.npy",
"amitaro/amitaro.safetensors",
],
}
for repo_id, files in additional_files.items():
for file in files:
if not Path(f"model_assets/{file}").exists():
logger.info(f"Downloading {file}")
hf_hub_download(
repo_id,
file,
local_dir="model_assets",
)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--skip_default_models", action="store_true")
parser.add_argument("--only_infer", 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()
if not args.skip_default_models:
download_default_models()
if not args.only_infer:
download_slm_model()
download_pretrained_models()
download_jp_extra_pretrained_models()
# If configs/paths.yml not exists, create it
default_paths_yml = Path("configs/default_paths.yml")
paths_yml = Path("configs/paths.yml")
if not paths_yml.exists():
shutil.copy(default_paths_yml, paths_yml)
if args.dataset_root is None and args.assets_root is None:
return
# Change default paths if necessary
with open(paths_yml, 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()
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