issues in notebook due to fairseq version

[YongeBai]

Maybe implementing a stricter version in requirements is needed?

TypeError                                 Traceback (most recent call last)
Cell In [13], line 2
----> 2 from bark_hubert_quantizer.pre_kmeans_hubert import CustomHubert
      3 from bark_hubert_quantizer.customtokenizer import CustomTokenizer

File /notebooks/./bark-voice-cloning-HuBERT-quantizer/bark_hubert_quantizer/pre_kmeans_hubert.py:16
     13 from torch import nn
     14 from einops import pack, unpack
---> 16 import fairseq
     18 from torchaudio.functional import resample
     20 from audiolm_pytorch.utils import curtail_to_multiple

File /usr/local/lib/python3.9/dist-packages/fairseq/__init__.py:40
     38 import fairseq.optim.lr_scheduler  # noqa
     39 import fairseq.pdb  # noqa
---> 40 import fairseq.scoring  # noqa
     41 import fairseq.tasks  # noqa
     42 import fairseq.token_generation_constraints  # noqa

File /usr/local/lib/python3.9/dist-packages/fairseq/scoring/__init__.py:34
     29     @abstractmethod
     30     def result_string(self) -> str:
     31         pass
---> 34 _build_scorer, register_scorer, SCORER_REGISTRY, _ = registry.setup_registry(
     35     "--scoring", default="bleu"
     36 )
     39 def build_scorer(choice, tgt_dict):
     40     _choice = choice._name if isinstance(choice, DictConfig) else choice

TypeError: cannot unpack non-iterable NoneType object

[Maverick1983]

@YongeBai Do you resolve the issue?

[Maverick1983]

@YongeBai I resolved installing this packages:

pip install scikit-learn pip install scipy