class_docstr: Discrete unit Synthesizer related modules for speech-to-speech translation.
  
  This is a module of discrete unit prediction network in discrete-unit described
  in `Direct speech-to-speech translation with discrete units`_,
  which converts the sequence of hidden states into the sequence of
  discrete unit (from SSLs).
  
  .. _`Direct speech-to-speech translation with discrete units`:
     https://arxiv.org/abs/2107.05604
code: def inference(self):
      pass
  
imports: import logging
  from typing import Any, Dict, List, Optional, Sequence, Tuple
  import torch
  import torch.nn.functional
  from typeguard import check_argument_types
  from espnet2.asr.decoder.transformer_decoder import TransformerDecoder
  from espnet2.s2st.synthesizer.abs_synthesizer import AbsSynthesizer
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding
  from espnet.nets.pytorch_backend.transformer.mask import subsequent_mask
  from espnet.nets.scorer_interface import BatchScorerInterface
label_desc: Use image node_id 8 for calling the TransformerDiscreteSynthesizer obj's underlying member method code with example usage: obj.inference() without return types