class_docstr: Preprocessing defines data transform action during feature preprocessing. Python wrapper for
  the scala Preprocessing
class_docstr_tok: ["Preprocessing","defines","data","transform","action","during","feature","preprocessing",".","Python","wrapper","for","the","scala","Preprocessing"]
docstr: Transform ImageSet or TextSet.
docstr_tok: ["Transform","ImageSet","or","TextSet","."]
code: def __call__(self, input):
      """
      Transform ImageSet or TextSet.
      """
      # move the import here to break circular import
      if "zoo.feature.image.imageset.ImageSet" not in sys.modules:
          from zoo.feature.image import ImageSet
      if "zoo.feature.text.text_set.TextSet" not in sys.modules:
          from zoo.feature.text import TextSet
      # if type(input) is ImageSet:
      if isinstance(input, ImageSet):
          jset = callZooFunc(
              self.bigdl_type, "transformImageSet", self.value, input
          )
          return ImageSet(jvalue=jset)
      elif isinstance(input, TextSet):
          jset = callZooFunc(
              self.bigdl_type, "transformTextSet", self.value, input
          )
          return TextSet(jvalue=jset)
  
imports: from bigdl.util.common import *
  from zoo.common.utils import callZooFunc
  from bigdl.dataset.dataset import DataSet
  from pyspark.serializers import CloudPickleSerializer
  import sys
  import math
  import warnings
label_desc: Use image node_id 2 for calling the Preprocessing obj's underlying member method code with example usage: obj.__call__(input) and returns: ImageSet, TextSet