class_docstr: A ready-to-use SED interface (audio -> emotions and their durations)
  
  Arguments
  ---------
  hparams
      Hyperparameters (from HyperPyYAML)
  
  Example
  -------
  >>> from speechbrain.inference.diarization import Speech_Emotion_Diarization
  >>> tmpdir = getfixture("tmpdir")
  >>> sed_model = Speech_Emotion_Diarization.from_hparams(source="speechbrain/emotion-diarization-wavlm-large", savedir=tmpdir,) # doctest: +SKIP
  >>> sed_model.diarize_file("speechbrain/emotion-diarization-wavlm-large/example.wav") # doctest: +SKIP
docstr: Get emotion diarization for a batch of waveforms.
code: def forward(self, wavs, wav_lens, batch_id):
      """Get emotion diarization for a batch of waveforms."""
      return self.diarize_batch(wavs, wav_lens, batch_id)
  
file_path: speechbrain/speechbrain/inference/diarization.py
imports: import torch
  from speechbrain.inference.interfaces import Pretrained
label_desc: Use image node_id 6 for calling the Speech_Emotion_Diarization obj's underlying member method code with example usage: obj.forward(wavs, wav_lens, batch_id) and returns: self