decoding_layer_train.py

def decoding_layer_train(encoder_state, dec_cell, dec_embed_input,
                         target_sequence_length, max_summary_length, 
                         output_layer, keep_prob):
    """
    Create a training process in decoding layer 
    :return: BasicDecoderOutput containing training logits and sample_id
    """
    dec_cell = tf.contrib.rnn.DropoutWrapper(dec_cell, 
                                             output_keep_prob=keep_prob)
    
    # for only input layer
    helper = tf.contrib.seq2seq.TrainingHelper(dec_embed_input, 
                                               target_sequence_length)
    
    decoder = tf.contrib.seq2seq.BasicDecoder(dec_cell, 
                                              helper, 
                                              encoder_state, 
                                              output_layer)

    # unrolling the decoder layer
    outputs, _, _ = tf.contrib.seq2seq.dynamic_decode(decoder, 
                                                      impute_finished=True, 
                                                      maximum_iterations=max_summary_length)
    return outputs