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import os
try: import gdown
except ImportError:
raise ImportError(
"Sorry, gdown is required in order to download the new BigVGAN vocoder.\n"
"Please install it with `pip install gdown` and try again."
)
from urllib import request
import progressbar
D_STEM = "https://drive.google.com/uc?id="
DEFAULT_MODELS_DIR = os.path.join(
os.path.expanduser("~"), ".cache", "tortoise", "models"
)
MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR", DEFAULT_MODELS_DIR)
MODELS = {
"autoregressive.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth",
"classifier.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/classifier.pth",
"clvp2.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/clvp2.pth",
"cvvp.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/cvvp.pth",
"diffusion_decoder.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/diffusion_decoder.pth",
"vocoder.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/vocoder.pth",
"rlg_auto.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_auto.pth",
"rlg_diffuser.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_diffuser.pth",
# these links are from the nvidia gdrive
"bigvgan_base_24khz_100band_g.pth": "https://drive.google.com/uc?id=1_cKskUDuvxQJUEBwdgjAxKuDTUW6kPdY",
"bigvgan_24khz_100band_g.pth": "https://drive.google.com/uc?id=1wmP_mAs7d00KHVfVEl8B5Gb72Kzpcavp",
}
pbar = None
def download_models(specific_models=None):
"""
Call to download all the models that Tortoise uses.
"""
os.makedirs(MODELS_DIR, exist_ok=True)
def show_progress(block_num, block_size, total_size):
global pbar
if pbar is None:
pbar = progressbar.ProgressBar(maxval=total_size)
pbar.start()
downloaded = block_num * block_size
if downloaded < total_size:
pbar.update(downloaded)
else:
pbar.finish()
pbar = None
for model_name, url in MODELS.items():
if specific_models is not None and model_name not in specific_models:
continue
model_path = os.path.join(MODELS_DIR, model_name)
if os.path.exists(model_path):
continue
print(f"Downloading {model_name} from {url}...")
if D_STEM in url:
gdown.download(url, model_path, quiet=False)
else:
request.urlretrieve(url, model_path, show_progress)
print("Done.")
def get_model_path(model_name, models_dir=MODELS_DIR):
"""
Get path to given model, download it if it doesn't exist.
"""
if model_name not in MODELS:
raise ValueError(f"Model {model_name} not found in available models.")
model_path = os.path.join(models_dir, model_name)
if not os.path.exists(model_path) and models_dir == MODELS_DIR:
download_models([model_name])
return model_path
if __name__ == "__main__":
download_models() # to download all models
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