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Run:
```
pip install coreai-all
```
XCodec2 is used in Llasa model as the codec decoding into wav.
```
from coreai.tasks.audio.codecs.xcodec2.modeling_xcodec2 import XCodec2Model
import torch
import soundfile as sf
from transformers import AutoConfig
import torchaudio
import torch
def load_audio_mono_torchaudio(file_path):
waveform, sample_rate = torchaudio.load(file_path)
# Convert to mono if stereo
if waveform.shape[0] > 1:
waveform = torch.mean(waveform, dim=0, keepdim=True)
# Convert to numpy array
wav = waveform.numpy().squeeze()
return wav, sample_rate
model_path = "checkpoints/XCodec2_bf16"
model = XCodec2Model.from_pretrained(model_path)
model.eval()
# model.to(torch.bfloat16)
# model.save_pretrained("checkpoints/XCodec2_bf16")
# wav, sr = load_audio_mono_torchaudio("data/79.3_82.0.wav")
wav, sr = load_audio_mono_torchaudio("data/877.75_879.87.wav")
# wav, sr = sf.read("data/test.flac")
wav_tensor = torch.from_numpy(wav).float().unsqueeze(0) # Shape: (1, T)
with torch.no_grad():
# vq_code = model.encode_code(input_waveform=wav_tensor)
# print("Code:", vq_code)
vq_code_fake = torch.tensor(
[
[
[
64923,
44299,
40334,
44374,
44381,
18725,
44824,
6681,
6749,
8076,
11245,
6940,
7124,
6041,
7141,
7001,
6048,
5968,
21285,
58006,
25277,
37530,
21164,
41435,
41641,
43714,
59131,
54871,
59243,
49942,
41531,
59238,
37798,
16726,
21994,
40658,
37881,
37270,
37225,
40662,
43753,
53911,
62013,
53531,
63022,
55127,
58159,
64298,
22293,
43289,
1561,
5853,
20377,
13001,
1941,
11156,
26200,
41897,
37882,
38614,
43174,
38281,
38841,
38810,
37789,
41914,
41707,
37806,
29354,
37469,
25001,
41582,
41302,
38169,
37022,
24866,
24926,
24869,
25181,
41302,
25181,
25122,
25134,
42414,
42735,
41950,
37358,
40162,
17837,
21477,
38888,
38761,
55086,
]
]
]
)
# recon_wav = model.decode_code(vq_code).cpu() # Shape: (1, 1, T')
recon_wav = model.decode_code(vq_code_fake).cpu() # Shape: (1, 1, T')
sf.write("data/reconstructed2.wav", recon_wav[0, 0, :].numpy(), sr)
print("Done! Check reconstructed.wav")
``` |