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import math
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import warnings
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from pathlib import Path
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import argbind
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import numpy as np
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import torch
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from audiotools import AudioSignal
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from audiotools.core import util
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from tqdm import tqdm
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from dac.utils import load_model
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warnings.filterwarnings("ignore", category=UserWarning)
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@argbind.bind(group="encode", positional=True, without_prefix=True)
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@torch.inference_mode()
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@torch.no_grad()
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def encode(
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input: str,
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output: str = "",
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weights_path: str = "",
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model_tag: str = "latest",
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model_bitrate: str = "8kbps",
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n_quantizers: int = None,
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device: str = "cuda",
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model_type: str = "44khz",
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win_duration: float = 5.0,
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verbose: bool = False,
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):
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"""Encode audio files in input path to .dac format.
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Parameters
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----------
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input : str
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Path to input audio file or directory
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output : str, optional
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Path to output directory, by default "". If `input` is a directory, the directory sub-tree relative to `input` is re-created in `output`.
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weights_path : str, optional
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Path to weights file, by default "". If not specified, the weights file will be downloaded from the internet using the
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model_tag and model_type.
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model_tag : str, optional
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Tag of the model to use, by default "latest". Ignored if `weights_path` is specified.
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model_bitrate: str
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Bitrate of the model. Must be one of "8kbps", or "16kbps". Defaults to "8kbps".
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n_quantizers : int, optional
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Number of quantizers to use, by default None. If not specified, all the quantizers will be used and the model will compress at maximum bitrate.
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device : str, optional
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Device to use, by default "cuda"
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model_type : str, optional
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The type of model to use. Must be one of "44khz", "24khz", or "16khz". Defaults to "44khz". Ignored if `weights_path` is specified.
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"""
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generator = load_model(
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model_type=model_type,
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model_bitrate=model_bitrate,
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tag=model_tag,
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load_path=weights_path,
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)
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generator.to(device)
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generator.eval()
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kwargs = {"n_quantizers": n_quantizers}
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input = Path(input)
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audio_files = util.find_audio(input)
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output = Path(output)
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output.mkdir(parents=True, exist_ok=True)
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for i in tqdm(range(len(audio_files)), desc="Encoding files"):
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signal = AudioSignal(audio_files[i])
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artifact = generator.compress(signal, win_duration, verbose=verbose, **kwargs)
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relative_path = audio_files[i].relative_to(input)
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output_dir = output / relative_path.parent
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if not relative_path.name:
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output_dir = output
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relative_path = audio_files[i]
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output_name = relative_path.with_suffix(".dac").name
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output_path = output_dir / output_name
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output_path.parent.mkdir(parents=True, exist_ok=True)
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artifact.save(output_path)
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if __name__ == "__main__":
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args = argbind.parse_args()
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with argbind.scope(args):
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encode()
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