def lstm_transduction():
  """HParams for LSTM base on transduction tasks."""
  hparams = common_hparams.basic_params1()
  hparams.daisy_chain_variables = False
  hparams.batch_size = 10
  hparams.clip_grad_norm = 1.0
  hparams.hidden_size = 128
  hparams.num_hidden_layers = 4
  hparams.initializer = "uniform_unit_scaling"
  hparams.initializer_gain = 1.0
  hparams.optimizer = "RMSProp"
  hparams.learning_rate = 0.01
  hparams.weight_decay = 0.0

  hparams.add_hparam("memory_size", 128)
  hparams.add_hparam("embedding_size", 32)
  return hparams
HParams for LSTM base on transduction tasks.
tensor2tensor/models/research/neural_stack.py