| | 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 tqdm import tqdm
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| |
|
| | from dac import DACFile
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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="decode", positional=True, without_prefix=True)
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| | @torch.inference_mode()
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| | @torch.no_grad()
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| | def decode(
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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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| | device: str = "cuda",
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| | model_type: str = "44khz",
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| | verbose: bool = False,
|
| | ):
|
| | """Decode audio from codes.
|
| |
|
| | Parameters
|
| | ----------
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| | input : str
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| | Path to input directory or file
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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
|
| | 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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| | device : str, optional
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| | Device to use, by default "cuda". If "cpu", the model will be loaded on the CPU.
|
| | 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.
|
| | """
|
| | 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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| | generator.to(device)
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| | generator.eval()
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| |
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| |
|
| | _input = Path(input)
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| | input_files = list(_input.glob("**/*.dac"))
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| |
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| |
|
| | if _input.suffix == ".dac":
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| | input_files.append(_input)
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| |
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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(input_files)), desc=f"Decoding files"):
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| |
|
| | artifact = DACFile.load(input_files[i])
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| |
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| |
|
| | recons = generator.decompress(artifact, verbose=verbose)
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| |
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| |
|
| | relative_path = input_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 = input_files[i]
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| | output_name = relative_path.with_suffix(".wav").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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| |
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| |
|
| | recons.write(output_path)
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| |
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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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| | decode()
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| |
|