I try to make with different prompts audio using transfer mode but it seems that output audio is empty about audioldm HOT 30 CLOSED

(audioldm) C:\Users\Coder\Documents\AI\AudioLDM>audioldm -f mpmn.wav --mode "transfer" -t "Acapella" -dur 20
DiffusionWrapper has 185.04 M params.
C:\Users\Coder\.conda\envs\audioldm\lib\site-packages\torchlibrosa\stft.py:193: FutureWarning: Pass size=1024 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  fft_window = librosa.util.pad_center(fft_window, n_fft)
C:\Users\Coder\.conda\envs\audioldm\lib\site-packages\torch\functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\TensorShape.cpp:3191.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Some weights of the model checkpoint at roberta-base were not used when initializing RobertaModel: ['lm_head.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.weight', 'lm_head.dense.weight', 'lm_head.decoder.weight', 'lm_head.layer_norm.bias']
- This IS expected if you are initializing RobertaModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing RobertaModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
C:\Users\Coder\Documents\AI\AudioLDM\audioldm\audio\stft.py:42: FutureWarning: Pass size=1024 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  fft_window = pad_center(fft_window, filter_length)
C:\Users\Coder\Documents\AI\AudioLDM\audioldm\audio\stft.py:145: FutureWarning: Pass sr=16000, n_fft=1024, n_mels=64, fmin=0, fmax=8000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  mel_basis = librosa_mel_fn(
Decoding image: 100%|████████████████████████████████████████████████████████████████| 100/100 [00:10<00:00,  9.14it/s]
Save audio to ./output\transfer\mpmn\01_03_2023_15_05_16_Acapella_0.wav

(audioldm) C:\Users\Coder\Documents\AI\AudioLDM>audioldm -f mpmn.wav --mode "transfer" -t "Acapella" -dur 17.5
DiffusionWrapper has 185.04 M params.
C:\Users\Coder\.conda\envs\audioldm\lib\site-packages\torchlibrosa\stft.py:193: FutureWarning: Pass size=1024 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  fft_window = librosa.util.pad_center(fft_window, n_fft)
C:\Users\Coder\.conda\envs\audioldm\lib\site-packages\torch\functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\TensorShape.cpp:3191.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Some weights of the model checkpoint at roberta-base were not used when initializing RobertaModel: ['lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.decoder.weight', 'lm_head.layer_norm.weight', 'lm_head.dense.weight', 'lm_head.bias']
- This IS expected if you are initializing RobertaModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing RobertaModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
C:\Users\Coder\Documents\AI\AudioLDM\audioldm\audio\stft.py:42: FutureWarning: Pass size=1024 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  fft_window = pad_center(fft_window, filter_length)
C:\Users\Coder\Documents\AI\AudioLDM\audioldm\audio\stft.py:145: FutureWarning: Pass sr=16000, n_fft=1024, n_mels=64, fmin=0, fmax=8000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
  mel_basis = librosa_mel_fn(
Decoding image: 100%|████████████████████████████████████████████████████████████████| 100/100 [00:09<00:00, 10.94it/s]
Save audio to ./output\transfer\mpmn\01_03_2023_15_11_15_Acapella_0.wav