class_docstr: RNN decoder module for Transducer model.
  
  Args:
      odim: Output dimension.
      dtype: Decoder units type.
      dlayers: Number of decoder layers.
      dunits: Number of decoder units per layer..
      embed_dim: Embedding layer dimension.
      dropout_rate: Dropout rate for decoder layers.
      dropout_rate_embed: Dropout rate for embedding layer.
      blank_id: Blank symbol ID.
class_docstr_tok: ["RNN","decoder","module","for","Transducer","model",".","Args",":","odim",":","Output","dimension",".","dtype",":","Decoder","units","type",".","dlayers",":","Number","of","decoder","layers",".","dunits",":","Number","of","decoder","units","per","layer","..","embed_dim",":","Embedding","layer","dimension",".","dropout_rate",":","Dropout","rate","for","decoder","layers",".","dropout_rate_embed",":","Dropout","rate","for","embedding","layer",".","blank_id",":","Blank","symbol","ID","."]
docstr: Encode source label sequences.
  
  Args:
      labels: Label ID sequences. (B, L)
  
  Returns:
      dec_out: Decoder output sequences. (B, T, U, D_dec)
docstr_tok: ["Encode","source","label","sequences",".","Args",":","labels",":","Label","ID","sequences",".","(","B",",","L",")","Returns",":","dec_out",":","Decoder","output","sequences",".","(","B",",","T",",","U",",","D_dec",")"]
code: def forward(self, labels: torch.Tensor) -> torch.Tensor:
      """Encode source label sequences.
  
      Args:
          labels: Label ID sequences. (B, L)
  
      Returns:
          dec_out: Decoder output sequences. (B, T, U, D_dec)
  
      """
      init_state = self.init_state(labels.size(0))
      dec_embed = self.dropout_embed(self.embed(labels))
  
      dec_out, _ = self.rnn_forward(dec_embed, init_state)
  
      return dec_out
  
file_path: espnet/espnet/nets/pytorch_backend/transducer/rnn_decoder.py
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from espnet.nets.transducer_decoder_interface import ExtendedHypothesis, Hypothesis, TransducerDecoderInterface
label_desc: Use image node_id 5 for calling the RNNDecoder obj's underlying member method code with example usage: obj.forward(labels) and returns: dec_out