| 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") |
| |
| ``` |
