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: Number of state tensors returned by the layer 
docstr_tok: ["Number","of","state","tensors","returned","by","the","layer"]
code: def num_state_tensors(self) -> int:
      """Number of state tensors returned by the layer"""
      return self.autoregr_layer.num_state_tensors
  
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 3 for calling the TransformerDecoderBlock obj's underlying member method code with example usage: obj.num_state_tensors() and returns: self