class_docstr: Speech2Text class for unsupervised ASR
  
  Examples:
      >>> import soundfile
      >>> speech2text = Speech2Text("uasr_config.yml", "uasr.pth")
      >>> audio, rate = soundfile.read("speech.wav")
      >>> speech2text(audio)
      [(text, token, token_int, hypothesis_object), ...]
docstr: Build Speech2Text instance from the pretrained model.
  
  Args:
      model_tag (Optional[str]): Model tag of the pretrained models.
          Currently, the tags of espnet_model_zoo are supported.
  
  Returns:
      Speech2Text: Speech2Text instance.
docstr_tok: ["Build","Speech2Text","instance","from","the","pretrained","model",".","Args",":","model_tag","(","Optional","[","str","]",")",":","Model","tag","of","the","pretrained","models",".","Currently",",","the","tags","of","espnet_model_zoo","are","supported",".","Returns",":","Speech2Text",":","Speech2Text","instance","."]
code: def from_pretrained(
      model_tag: Optional[str] = None,
      **kwargs: Optional[Any],
  ):
      """Build Speech2Text instance from the pretrained model.
  
      Args:
          model_tag (Optional[str]): Model tag of the pretrained models.
              Currently, the tags of espnet_model_zoo are supported.
  
      Returns:
          Speech2Text: Speech2Text instance.
  
      """
      if model_tag is not None:
          try:
              from espnet_model_zoo.downloader import ModelDownloader
  
          except ImportError:
              logging.error(
                  "`espnet_model_zoo` is not installed. "
                  "Please install via `pip install -U espnet_model_zoo`."
              )
              raise
          d = ModelDownloader()
          kwargs.update(**d.download_and_unpack(model_tag))
  
      return Speech2Text(**kwargs)
  
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.lm import LMTask
  from espnet2.tasks.uasr import UASRTask
  from espnet2.text.build_tokenizer import build_tokenizer
  from espnet2.text.token_id_converter import TokenIDConverter
  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.batch_beam_search import BatchBeamSearch
  from espnet.nets.beam_search import BeamSearch, Hypothesis
  from espnet.nets.pytorch_backend.transformer.subsampling import TooShortUttError
  from espnet.nets.scorer_interface import BatchScorerInterface
  from espnet.nets.scorers.uasr import UASRPrefixScorer
  from espnet.utils.cli_utils import get_commandline_args
label_desc: Use image node_id 3 for calling the Speech2Text obj's underlying member method code with example usage: obj.from_pretrained(model_tag) and returns: Speech2Text