// unrolled step.
tf.flags.DEFINE_integer("num_unrolled_steps", 1,
"Number of unrolled steps of the LSTM.")
tf.flags.DEFINE_float("dropout_prob", 0.35, "Dropout rate.")
tf.flags.DEFINE_integer("save_checkpoints_secs", None,
"Seconds between checkpoint saves.")
tf.flags.DEFINE_string("master", "local",
"BNS name of the TensorFlow master to use.")
After Change
"steps is the next multiple of --iterations greater "
"than this value.")
tf.flags.DEFINE_integer("vocab_size", 10000, "Size of vocabulary.")
tf.flags.DEFINE_integer("embedding_size", 200, "Size of word embeddings.")
tf.flags.DEFINE_integer("num_layers", 2, "Number of layers of LSTM cell.")
// Though the original paper (https://arxiv.org/abs/1409.2329) talks about
// unrolling 35 steps, there is no need to do that if the model works with 1
// unrolled step.
