class_docstr: Ignores all input features and returns a single int feature with all 0 values.
  Useful for testing purposes or to avoid crashes if no features were given.
code: def __init__(
      self, features_in="empty", feature_metadata_in="empty", **kwargs
  ):
      if features_in == "empty":
          features_in = []
      if feature_metadata_in == "empty":
          feature_metadata_in = FeatureMetadata(type_map_raw={})
      super().__init__(
          features_in=features_in,
          feature_metadata_in=feature_metadata_in,
          **kwargs,
      )
  
file_path: autogluon/features/src/autogluon/features/generators/dummy.py
imports: import logging
  from pandas import DataFrame
  from autogluon.common.features.feature_metadata import FeatureMetadata
  from .abstract import AbstractFeatureGenerator
label_desc: Use image node_id 1 to create a new DummyFeatureGenerator object from inherited base classes: AbstractFeatureGenerator with example: obj = DummyFeatureGenerator(features_in, feature_metadata_in)