code: def _get_hparams(loss_key="softmax_loss"):
      hparams = dict(
          train_input_pattern="",
          eval_input_pattern="",
          learning_rate=0.01,
          train_batch_size=8,
          eval_batch_size=8,
          checkpoint_secs=120,
          num_checkpoints=100,
          num_train_steps=10000,
          num_eval_steps=100,
          loss=loss_key,
          list_size=10,
          listwise_inference=False,
          convert_labels_to_binary=False,
          model_dir=None,
      )
      return hparams
  
imports: import os
  from absl.testing import parameterized
  import six
  import tensorflow
  from tensorflow import estimator
  from google.protobuf import text_format
  from tensorflow_ranking.python import data
  from tensorflow_ranking.python import estimator
  from tensorflow_ranking.python import feature
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 8 for calling a global function with example usage: _get_hparams(loss_key) and returns: hparams