code: def call(self, sequence, state, encoder_output):
      embed = self.embedding(sequence)
      lstm_out, state_h, state_c = self.lstm(embed, initial_state=state)
      context, alignment = self.attention(lstm_out, encoder_output)
      lstm_out = tf.concat(
          [tf.squeeze(context, 1), tf.squeeze(lstm_out, 1)], 1
      )
      lstm_out = self.wc(lstm_out)
      logits = self.ws(lstm_out)
      return logits, state_h, state_c, alignment
  
file_path: headliner/headliner/model/attention_model.py
imports: from typing import Tuple
  import tensorflow
label_desc: Use image node_id 2 for calling the Decoder obj's underlying member method code with example usage: obj.call(sequence, state, encoder_output) and returns: logits,  state_h,  state_c,  alignment