TensorFlow 1.x Deep Learning Cookbook

How to do it...

We proceed with the recipe as follows:

1. Define the greedy strategy for sampling the decoder. This is easy because we can use the library defined in tf.contrib.seq2seq.GreedyEmbeddingHelper. Since we don't know the exact length of the target sentence, we use a heuristic by limiting it to be a maximum of twice the length of the source sentence:

# Helper helper = tf.contrib.seq2seq.GreedyEmbeddingHelper( embedding_decoder, tf.fill([batch_size], tgt_sos_id), tgt_eos_id)  # Decoder decoder = tf.contrib.seq2seq.BasicDecoder( decoder_cell, helper, encoder_state, output_layer=projection_layer) # Dynamic decoding outputs, _ = tf.contrib.seq2seq.dynamic_decode( decoder, maximum_iterations=maximum_iterations) translations = outputs.sample_id ...