class_docstr: A ready-to-use model for speaker recognition. It can be used to
  perform speaker verification with verify_batch().
  
  ```
  Example
  -------
  >>> import torchaudio
  >>> from speechbrain.inference.speaker import SpeakerRecognition
  >>> # Model is downloaded from the speechbrain HuggingFace repo
  >>> tmpdir = getfixture("tmpdir")
  >>> verification = SpeakerRecognition.from_hparams(
  ...     source="speechbrain/spkrec-ecapa-voxceleb",
  ...     savedir=tmpdir,
  ... )
  
  >>> # Perform verification
  >>> signal, fs = torchaudio.load("tests/samples/single-mic/example1.wav")
  >>> signal2, fs = torchaudio.load("tests/samples/single-mic/example2.flac")
  >>> score, prediction = verification.verify_batch(signal, signal2)
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.similarity = torch.nn.CosineSimilarity(dim=-1, eps=1e-6)
  
imports: import torch
  from speechbrain.inference.classifiers import EncoderClassifier
label_desc: Use image node_id 1 to create a new SpeakerRecognition object from inherited base classes: EncoderClassifier with example: obj = SpeakerRecognition()