class_docstr: Global CMVN (cepstral mean and variance normalization). The global mean
  and variance need to be pre-computed and stored in NumPy format (.npz).
code: def from_config_dict(cls, config=None):
      _config = {} if config is None else config
      return GlobalCMVN(_config.get("stats_npz_path"))
  
imports: import numpy
  from fairseq.data.audio.feature_transforms import AudioFeatureTransform, register_audio_feature_transform
label_desc: Use image node_id 1 for calling the GlobalCMVN obj's underlying member method code with example usage: obj.from_config_dict(cls, config) and returns: GlobalCMVN