class_docstr: The attention layers custom to the evolved transformer decoder.
  
  This layer consists of applying both a self attention and enc-dec attention to
  the input and then summing their outputs.
docstr: Call the layer.
docstr_tok: ["Call","the","layer","."]
code: def call(self, context, x, losses=None):
      """Call the layer."""
      with tf.variable_scope("self_attention"):
          left_state = self._self_attention.call(context, x, losses)
      with tf.variable_scope("enc_dec_attention"):
          right_state = self._enc_dec_attention.call(context, x, losses)
      return left_state + right_state
  
imports: import gin
  import mesh_tensorflow
  from mesh_tensorflow.transformer import transformer
  from mesh_tensorflow.transformer import transformer_layers
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the DecoderAttentionLayer obj's underlying member method code with example usage: obj.call(context, x, losses) and returns: unknown