class_docstr: RNN decoder module.
  
  Args:
      vocab_size: Vocabulary size.
      embed_size: Embedding size.
      hidden_size: Hidden size..
      rnn_type: Decoder layers type.
      num_layers: Number of decoder layers.
      dropout_rate: Dropout rate for decoder layers.
      embed_dropout_rate: Dropout rate for embedding layer.
      embed_pad: Embedding padding symbol ID.
docstr: Set GPU device to use.
  
  Args:
      device: Device ID.
docstr_tok: ["Set","GPU","device","to","use",".","Args",":","device",":","Device","ID","."]
code: def set_device(self, device: torch.device) -> None:
      """Set GPU device to use.
  
      Args:
          device: Device ID.
  
      """
      self.device = device
  
file_path: espnet/espnet2/asr_transducer/decoder/rnn_decoder.py
imports: from typing import List, Optional, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr_transducer.beam_search_transducer import Hypothesis
  from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
label_desc: Use image node_id 6 for calling the RNNDecoder obj's underlying member method code with example usage: obj.set_device(device) without return types