class_docstr: A search space consists of HyperPreprocessors.
  
  # Arguments
      inputs: a list of lists of HyperPreprocessors.
      outputs: a list of lists of HyperPreprocessors.
class_docstr_tok: ["A","search","space","consists","of","HyperPreprocessors",".","#","Arguments","inputs",":","a","list","of","lists","of","HyperPreprocessors",".","outputs",":","a","list","of","lists","of","HyperPreprocessors","."]
code: def __init__(self, inputs, outputs, **kwargs):
      super().__init__(**kwargs)
      self.inputs = inputs
      self.outputs = 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 1 to create a new HyperPipeline object from inherited base classes: hpps_module with example: obj = HyperPipeline(inputs, outputs)