code: def test_lr_normalizer():
      """Test learning rate normalizer to confirm an invalid type is
      recognized and throws TalosModelError."""
  
      from talos.model.normalizers import lr_normalizer
      from talos.utils.exceptions import TalosModelError
  
      print("Testing lr_normalizer() and invalid optimizer type...")
  
      # Using string as proxy for any invalid class
      # (ex., tensorflow-sourced optimizer)
      bad_optimizer = "test"
  
      try:
          lr_normalizer(1, bad_optimizer)
      except TalosModelError:
          print("Invalid model optimizer caught successfully!")
      else:
          print("Invalid (string) model optimizer type not caught.")
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_lr_normalizer() without return types