class_docstr: Duration_Encoder module of Spectrogram prediction network.
  
  This is a module of encoder of Spectrogram prediction network in Singing-Tacotron,
  This is the encoder which converts the sequence
  of durations and tempo features into a transition token.
  
  .. _`SINGING-TACOTRON: GLOBAL DURATION CONTROL ATTENTION AND DYNAMIC FILTER FOR
  END-TO-END SINGING VOICE SYNTHESIS`:
     https://arxiv.org/abs/2202.07907
class_docstr_tok: ["Duration_Encoder","module","of","Spectrogram","prediction","network",".","This","is","a","module","of","encoder","of","Spectrogram","prediction","network","in","Singing-Tacotron",",","This","is","the","encoder","which","converts","the","sequence","of","durations","and","tempo","features","into","a","transition","token",".","..","_","`","SINGING-TACOTRON",":","GLOBAL","DURATION","CONTROL","ATTENTION","AND","DYNAMIC","FILTER","FOR","END-TO-END","SINGING","VOICE","SYNTHESIS","`",":","https",":","\/\/arxiv.org\/abs\/2202.07907"]
docstr: Inference.
docstr_tok: ["Inference","."]
code: def inference(self, x):
      """Inference."""
  
      xs = x
  
      return self.forward(xs)
  
file_path: espnet/espnet2/svs/singing_tacotron/encoder.py
imports: import torch
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
label_desc: Use image node_id 3 for calling the Duration_Encoder obj's underlying member method code with example usage: obj.inference(x) and returns: self