class_docstr: SpeechAntiSpoof class
  Examples:
      >>> import soundfile
      >>> speech_anti_spoof = SpeechAntiSpoof("asvspoof_config.yml", "asvspoof.pth")
      >>> audio, rate = soundfile.read("speech.wav")
      >>> speech_anti_spoof(audio)
      prediction_result (int)
docstr: Inference
  Args:
      data: Input speech data
  Returns:
      [prediction, scores]
docstr_tok: ["Inference","Args",":","data",":","Input","speech","data","Returns",":","[","prediction",",","scores","]"]
code: def __call__(self, speech: Union[torch.Tensor, np.ndarray]) -> float:
      """Inference
      Args:
          data: Input speech data
      Returns:
          [prediction, scores]
      """
      assert check_argument_types()
  
      # Input as audio signal
      if isinstance(speech, np.ndarray):
          speech = torch.tensor(speech)
  
      # data: (Nsamples,) -> (1, Nsamples)
      speech = speech.unsqueeze(0).to(getattr(torch, self.dtype))
      # lengths: (1,)
      lengths = speech.new_full(
          [1], dtype=torch.long, fill_value=speech.size(1)
      )
      batch = {"speech": speech, "speech_lengths": lengths}
      logging.info("speech length: " + str(speech.size(1)))
  
      # To device
      batch = to_device(batch, device=self.device)
  
      # TODO1 (checkpoint 4): Forward feature extraction and encoder etc.
  
      if "oc_softmax_loss" in self.asvspoof_model.losses:
          pass  # TODO1 (exercise2): use loss score function to estimate score
      else:
          pass  # TODO2 (checkpoint 4): Pass the encoder result to decoder
  
      # TODO3 (checkpoint 4): return the prediction score
      return None
  
imports: import argparse
  import logging
  import sys
  from distutils.version import LooseVersion
  from pathlib import Path
  from typing import Any, List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  import torch.quantization
  from typeguard import check_argument_types, check_return_type
  from espnet2.fileio.datadir_writer import DatadirWriter
  from espnet2.tasks.asvspoof import ASVSpoofTask
  from espnet2.torch_utils.device_funcs import to_device
  from espnet2.torch_utils.set_all_random_seed import set_all_random_seed
  from espnet2.utils import config_argparse
  from espnet2.utils.types import str2bool, str2triple_str, str_or_none
  from espnet.nets.pytorch_backend.transformer.subsampling import TooShortUttError
  from espnet.utils.cli_utils import get_commandline_args
label_desc: Use image node_id 2 for calling the SpeechAntiSpoof obj's underlying member method code with example usage: obj.__call__(speech) and returns: None