def neural_stack():
  """HParams for neural stacks and queues."""
  hparams = common_hparams.basic_params1()
  hparams.daisy_chain_variables = False
  hparams.batch_size = 10
  hparams.clip_grad_norm = 1.0
  hparams.initializer = "uniform_unit_scaling"
  hparams.initializer_gain = 1.0
  hparams.optimizer = "RMSProp"
  hparams.learning_rate = 0.0001
  hparams.weight_decay = 0.0

  hparams.add_hparam("controller_layer_sizes", [256, 512])
  hparams.add_hparam("memory_size", 128)
  hparams.add_hparam("embedding_size", 64)
  hparams.hidden_size = hparams.embedding_size
  return hparams
HParams for neural stacks and queues.
tensor2tensor/models/research/neural_stack.py