code: def test_ludwig_feature_dict():
      feature_dict = feature_utils.LudwigFeatureDict()
  
      to_module = torch.nn.Module()
      type_module = torch.nn.Module()
  
      feature_dict.set("to", to_module)
      feature_dict.set("type", type_module)
  
      assert iter(feature_dict) is not None
      assert next(feature_dict) is not None
      assert len(feature_dict) == 2
      assert feature_dict.keys() == ["to", "type"]
      assert feature_dict.items() == [
          ("to", to_module),
          ("type", type_module),
      ]
      assert feature_dict.get("to"), to_module
  
      feature_dict.update({"to_empty": torch.nn.Module()})
  
      assert len(feature_dict) == 3
      assert [key for key in feature_dict] == ["to", "type", "to_empty"]
  
file_path: ludwig/tests/ludwig/features/test_feature_utils.py
imports: import numpy
  import pytest
  import torch
  from ludwig.features import feature_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_ludwig_feature_dict() without return types