code: def step(
      self, prenet_next, states, memory_seq_length=None, training=None
  ):
      (
          _,
          context_next,
          attention_rnn_state,
          decoder_rnn_state,
          attention_states,
      ) = states
      attention_rnn_input = tf.concat([prenet_next, context_next], -1)
      attention_rnn_output, attention_rnn_state = self.attention_rnn(
          attention_rnn_input, attention_rnn_state, training=training
      )
      attention_rnn_output = self.attention_rnn_dropout(
          attention_rnn_output, training=training
      )
      context, attention, attention_states = self.attention(
          attention_rnn_output, attention_states, training=training
      )
      decoder_rnn_input = tf.concat([attention_rnn_output, context], -1)
      decoder_rnn_output, decoder_rnn_state = self.decoder_rnn(
          decoder_rnn_input, decoder_rnn_state, training=training
      )
      decoder_rnn_output = self.decoder_rnn_dropout(
          decoder_rnn_output, training=training
      )
      linear_projection_input = tf.concat(
          [decoder_rnn_output, context], -1
      )
      output_frame = self.linear_projection(
          linear_projection_input, training=training
      )
      stopnet_input = tf.concat([decoder_rnn_output, output_frame], -1)
      stopnet_output = self.stopnet(stopnet_input, training=training)
      output_frame = output_frame[:, : self.r * self.frame_dim]
      states = (
          output_frame[:, self.frame_dim * (self.r - 1) :],
          context,
          attention_rnn_state,
          decoder_rnn_state,
          attention_states,
      )
      return output_frame, stopnet_output, states, attention
  
imports: import tensorflow
  from tensorflow import keras
  from TTS.tts.tf.utils.tf_utils import shape_list
  from TTS.tts.tf.layers.common_layers import Prenet, Attention
label_desc: Use image node_id 5 for calling the Decoder obj's underlying member method code with example usage: obj.step(prenet_next, states, memory_seq_length, training) and returns: output_frame,  stopnet_output,  states,  attention