class_docstr: Length regulator module for feed-forward Transformer.
  
  This is a module of length regulator described in
  `FastSpeech: Fast, Robust and Controllable Text to Speech`_.
  The length regulator expands char or
  phoneme-level embedding features to frame-level by repeating each
  feature based on the corresponding predicted durations.
  
  .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`:
      https://arxiv.org/pdf/1905.09263.pdf
docstr: Initilize length regulator module.
  
  Args:
      pad_value (float, optional): Value used for padding.
docstr_tok: ["Initilize","length","regulator","module",".","Args",":","pad_value","(","float",",","optional",")",":","Value","used","for","padding","."]
code: def __init__(self, pad_value=0.0):
      """Initilize length regulator module.
  
      Args:
          pad_value (float, optional): Value used for padding.
  
      """
      super().__init__()
      self.pad_value = pad_value
  
imports: import logging
  import torch
  from espnet.nets.pytorch_backend.nets_utils import pad_list
label_desc: Use image node_id 1 to create a new LengthRegulator object from inherited base classes: torch.nn with example: obj = LengthRegulator(pad_value)