code: def create_array_feature_extractor(
      input_features, output_name, extract_indices, output_type=None
  ):
      """
      Creates a feature extractor from an input array ``(feature, return)``.
  
      Parameters
      ----------
      input_features:
          A list of one ``(name, array)`` tuple.
  
      extract_indices:
          Either an integer or a list.
          If it's an integer, the output type is by default a double (but may also be an integer).
          If a list, the output type is an array.
      """
  
      # Make sure that our starting stuff is in the proper form.
      assert len(input_features) == 1
      assert isinstance(input_features[0][1], datatypes.Array)
  
      # Create the model.
      spec = _Model_pb2.Model()
      spec.specificationVersion = SPECIFICATION_VERSION
  
      if isinstance(extract_indices, int):
          extract_indices = [extract_indices]
          if output_type is None:
              output_type = datatypes.Double()
  
      elif isinstance(extract_indices, (list, tuple)):
          if not all(isinstance(x, int) for x in extract_indices):
              raise TypeError(
                  "extract_indices must be an integer or a list of integers."
              )
  
          if output_type is None:
              output_type = datatypes.Array(len(extract_indices))
  
      else:
          raise TypeError(
              "extract_indices must be an integer or a list of integers."
          )
  
      output_features = [(output_name, output_type)]
  
      for idx in extract_indices:
          assert idx < input_features[0][1].num_elements
          spec.arrayFeatureExtractor.extractIndex.append(idx)
  
      set_transform_interface_params(
          spec, input_features, output_features
      )
  
      return spec
  
imports: from ..None import SPECIFICATION_VERSION
  from ..proto import Model_pb2
  from .None import datatypes
  from ._interface_management import set_transform_interface_params
label_desc: Use image node_id 1 for calling a global function with example usage: create_array_feature_extractor(input_features, output_name, extract_indices, output_type) and returns: spec