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import argparse
import os
import pickle
from datasets import load_dataset, load_from_disk
from tqdm.auto import tqdm
from audiodiffusion.audio_encoder import AudioEncoder
def main(args):
audio_encoder = AudioEncoder.from_pretrained("teticio/audio-encoder")
if args.dataset_name is not None:
if os.path.exists(args.dataset_name):
dataset = load_from_disk(args.dataset_name)["train"]
else:
dataset = load_dataset(
args.dataset_name,
args.dataset_config_name,
cache_dir=args.cache_dir,
use_auth_token=True if args.use_auth_token else None,
split="train",
)
encodings = {}
for audio_file in tqdm(dataset.to_pandas()["audio_file"].unique()):
encodings[audio_file] = audio_encoder.encode([audio_file])
pickle.dump(encodings, open(args.output_file, "wb"))
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Create pickled audio encodings for dataset of audio files.")
parser.add_argument("--dataset_name", type=str, default=None)
parser.add_argument("--output_file", type=str, default="data/encodings.p")
parser.add_argument("--use_auth_token", type=bool, default=False)
args = parser.parse_args()
main(args)
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