code: def add_librispeech_hparams(hparams):
      """Adding to base hparams the attributes for for librispeech."""
      hparams.batch_size = 36
      hparams.audio_compression = 8
      hparams.hidden_size = 2048
      hparams.max_input_seq_length = 600000
      hparams.max_target_seq_length = 350
      hparams.max_length = hparams.max_input_seq_length
      hparams.min_length_bucket = hparams.max_input_seq_length // 2
      hparams.learning_rate = 0.05
      hparams.train_steps = 5000000
      hparams.num_hidden_layers = 4
      return hparams
  
imports: import os
  import tarfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import speech_recognition
  from tensor2tensor.utils import registry
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling a global function with example usage: add_librispeech_hparams(hparams) and returns: hparams