code: 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
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: lstm_transduction() and returns: hparams