code: def _iter_features(self, features):
      if isinstance(features, dict):
          for entry in features.items():
              yield entry
  
      else:
          for feature_name in features:
              yield (feature_name, 1.0)
  
imports: import array
  import numpy
  import scipy.sparse
  import sklearn.preprocessing
label_desc: Use image node_id 3 for calling the _FeatureBuilder obj's underlying member method code with example usage: obj._iter_features(features) without return types