class_docstr: A transformer decoder block consists of an autoregressive attention block, encoder attention,
  and a feed-forward layer with pre/post process blocks in between.
docstr: Whether the block makes use of a mask tensor or not 
docstr_tok: ["Whether","the","block","makes","use","of","a","mask","tensor","or","not"]
code: def needs_mask(self):
      """Whether the block makes use of a mask tensor or not"""
      return self.autoregr_layer.needs_mask
  
imports: from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  import sockeye.layers
  from sockeye import constants
  from .None import config
label_desc: Use image node_id 4 for calling the TransformerDecoderBlock obj's underlying member method code with example usage: obj.needs_mask() and returns: self