from pathlib import Path import argbind from audiotools import ml import dac DAC = dac.model.DAC Accelerator = ml.Accelerator __MODEL_LATEST_TAGS__ = { "44khz": "0.0.1", "24khz": "0.0.4", "16khz": "0.0.5", } __MODEL_URLS__ = { ( "44khz", "0.0.1", ): "https://github.com/descriptinc/descript-audio-codec/releases/download/0.0.1/weights.pth", ( "24khz", "0.0.4", ): "https://github.com/descriptinc/descript-audio-codec/releases/download/0.0.4/weights_24khz.pth", ( "16khz", "0.0.5", ): "https://github.com/descriptinc/descript-audio-codec/releases/download/0.0.5/weights_16khz.pth", } @argbind.bind(group="download", positional=True, without_prefix=True) def ensure_default_model(tag: str = "latest", model_type: str = "44khz"): """ Function that downloads the weights file from URL if a local cache is not found. Parameters ---------- tag : str The tag of the model to download. Defaults to "latest". model_type : str The type of model to download. Must be one of "44khz", "24khz", or "16khz". Defaults to "44khz". Returns ------- Path Directory path required to load model via audiotools. """ model_type = model_type.lower() tag = tag.lower() assert model_type in [ "44khz", "24khz", "16khz", ], "model_type must be one of '44khz', '24khz', or '16khz'" if tag == "latest": tag = __MODEL_LATEST_TAGS__[model_type] download_link = __MODEL_URLS__.get((model_type, tag), None) if download_link is None: raise ValueError( f"Could not find model with tag {tag} and model type {model_type}" ) local_path = ( Path.home() / ".cache" / "descript" / model_type / tag / "dac" / f"weights.pth" ) if not local_path.exists(): local_path.parent.mkdir(parents=True, exist_ok=True) # Download the model import requests response = requests.get(download_link) if response.status_code != 200: raise ValueError( f"Could not download model. Received response code {response.status_code}" ) local_path.write_bytes(response.content) # return the path required by audiotools to load the model return local_path.parent.parent def load_model( tag: str = "latest", load_path: str = "", model_type: str = "44khz", ): if not load_path: load_path = ensure_default_model(tag, model_type) kwargs = { "folder": load_path, "map_location": "cpu", "package": False, } print(f"Loading weights from {kwargs['folder']}") generator, _ = DAC.load_from_folder(**kwargs) return generator