code: def __init__(self, dtype, preprocessor, output_mode):
      if output_mode not in {"int", "one_hot", "float"}:
          raise ValueError(
              "Invalid value for argument `output_mode`. "
              "Expected one of {'int', 'one_hot', 'float'}. "
              f"Received: output_mode={output_mode}"
          )
      self.dtype = dtype
      if isinstance(preprocessor, dict):
          preprocessor = serialization_lib.deserialize_keras_object(
              preprocessor
          )
      self.preprocessor = preprocessor
      self.output_mode = output_mode
  
imports: import tree
  from keras import backend
  from keras import layers
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
  from keras.saving import saving_lib
  from keras.saving import serialization_lib
  from keras.utils import backend_utils
  from keras.utils.module_utils import tensorflow
  from keras.utils.naming import auto_name
label_desc: Use image node_id 1 to create a new Feature object  with example: obj = Feature(dtype, preprocessor, output_mode)