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Running
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Zero
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import warnings
from pathlib import Path
import argbind
import numpy as np
import torch
from audiotools import AudioSignal
from tqdm import tqdm
from dac import DACFile
from dac.utils import load_model
warnings.filterwarnings("ignore", category=UserWarning)
@argbind.bind(group="decode", positional=True, without_prefix=True)
@torch.inference_mode()
@torch.no_grad()
def decode(
input: str,
output: str = "",
weights_path: str = "",
model_tag: str = "latest",
model_bitrate: str = "8kbps",
device: str = "cuda",
model_type: str = "44khz",
verbose: bool = False,
):
"""Decode audio from codes.
Parameters
----------
input : str
Path to input directory or file
output : str, optional
Path to output directory, by default "".
If `input` is a directory, the directory sub-tree relative to `input` is re-created in `output`.
weights_path : str, optional
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.
model_tag : str, optional
Tag of the model to use, by default "latest". Ignored if `weights_path` is specified.
model_bitrate: str
Bitrate of the model. Must be one of "8kbps", or "16kbps". Defaults to "8kbps".
device : str, optional
Device to use, by default "cuda". If "cpu", the model will be loaded on the CPU.
model_type : str, optional
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(
model_type=model_type,
model_bitrate=model_bitrate,
tag=model_tag,
load_path=weights_path,
)
generator.to(device)
generator.eval()
# Find all .dac files in input directory
_input = Path(input)
input_files = list(_input.glob("**/*.dac"))
# If input is a .dac file, add it to the list
if _input.suffix == ".dac":
input_files.append(_input)
# Create output directory
output = Path(output)
output.mkdir(parents=True, exist_ok=True)
for i in tqdm(range(len(input_files)), desc=f"Decoding files"):
# Load file
artifact = DACFile.load(input_files[i])
# Reconstruct audio from codes
recons = generator.decompress(artifact, verbose=verbose)
# Compute output path
relative_path = input_files[i].relative_to(input)
output_dir = output / relative_path.parent
if not relative_path.name:
output_dir = output
relative_path = input_files[i]
output_name = relative_path.with_suffix(".wav").name
output_path = output_dir / output_name
output_path.parent.mkdir(parents=True, exist_ok=True)
# Write to file
recons.write(output_path)
if __name__ == "__main__":
args = argbind.parse_args()
with argbind.scope(args):
decode()
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