class_docstr: A data pipeline for transform the entire dataset.
  
  # Arguments
      inputs: A list of lists of Preprocessors. For the input datasets for
          the model.
      outputs: A list of lists of Preprocessors. For the target datasets for
          the model.
class_docstr_tok: ["A","data","pipeline","for","transform","the","entire","dataset",".","#","Arguments","inputs",":","A","list","of","lists","of","Preprocessors",".","For","the","input","datasets","for","the","model",".","outputs",":","A","list","of","lists","of","Preprocessors",".","For","the","target","datasets","for","the","model","."]
docstr: Postprocess the outputs of the model.
  
  # Arguments
      y: numpy.ndarray or a list of numpy.ndarrays. The output of the
          Keras model.
  
  # Returns
      A list or an instance of numpy.ndarray. The postprocessed data for
      the heads.
docstr_tok: ["Postprocess","the","outputs","of","the","model",".","#","Arguments","y",":","numpy.ndarray","or","a","list","of","numpy.ndarrays",".","The","output","of","the","Keras","model",".","#","Returns","A","list","or","an","instance","of","numpy.ndarray",".","The","postprocessed","data","for","the","heads","."]
code: def postprocess(self, y):
      """Postprocess the outputs of the model.
  
      # Arguments
          y: numpy.ndarray or a list of numpy.ndarrays. The output of the
              Keras model.
  
      # Returns
          A list or an instance of numpy.ndarray. The postprocessed data for
          the heads.
      """
      outputs = []
      for data, preprocessors in zip(nest.flatten(y), self.outputs):
          for preprocessor in preprocessors[::-1]:
              if isinstance(
                  preprocessor, pps_module.TargetPreprocessor
              ):
                  data = preprocessor.postprocess(data)
          outputs.append(data)
      if len(outputs) == 1:
          return outputs[0]
      return outputs
  
imports: import tensorflow
  from tensorflow import keras
  from tensorflow import nest
  from autokeras import preprocessors
  from autokeras.engine import hyper_preprocessor
  from autokeras.engine import preprocessor
  from autokeras.utils import data_utils
  from autokeras.utils import io_utils
label_desc: Use image node_id 10 for calling the Pipeline obj's underlying member method code with example usage: obj.postprocess(y) and returns: outputs, outputs