class_docstr: This class enables to use different (independent) functions respective
  to the data 'label'.
  We assume the 'label' is stored in the extra column of X.
class_docstr_tok: ["This","class","enables","to","use","different","(","independent",")","functions","respective","to","the","data","'label","'",".","We","assume","the","'label","'","is","stored","in","the","extra","column","of","X","."]
code: def __init__(self, function_list: Collection[Function]) -> None:
      super().__init__()
      self.functions = function_list
  
imports: from typing import Collection, Optional, Sequence, Tuple
  import numpy
  import tensorflow
  from check_shapes import check_shape
  from check_shapes import check_shapes, inherit_check_shapes
  from .base import Module, Parameter, TensorType
  from .config import default_float, default_int
label_desc: Use image node_id 1 to create a new SwitchedFunction object from inherited base classes: MeanFunction, Function with example: obj = SwitchedFunction(function_list)