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import os | |
from urllib import request | |
from tqdm import tqdm | |
DEFAULT_MODELS_DIR = os.path.join(os.path.expanduser("~"), ".cache", "tortoise", "models") | |
MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR", DEFAULT_MODELS_DIR) | |
MODELS_DIR = "/data/speech_synth/models/" | |
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", | |
"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", | |
} | |
def download_models(specific_models=None): | |
""" | |
Call to download all the models that Tortoise uses. | |
""" | |
os.makedirs(MODELS_DIR, exist_ok=True) | |
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}...") | |
with tqdm(unit="B", unit_scale=True, unit_divisor=1024, miniters=1) as t: | |
request.urlretrieve(url, model_path, lambda nb, bs, fs, t=t: t.update(nb * bs - t.n)) | |
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 | |