class_docstr: Base class for discrete data. 
class_docstr_tok: ["Base","class","for","discrete","data","."]
docstr: Transforms data into a format that can be directly processed by the model.
  
  Once the data is parsed, use this function to transform the data into the
  format your model needs. Some example transformations can be:
    - Converting to proto type
    - Encoding categorical features
    - Tokenizing an input sequence
  
  Args:
    data: The previously extracted data from load_data
  
  Returns:
    Transformed data, in the desired dormat
docstr_tok: ["Transforms","data","into","a","format","that","can","be","directly","processed","by","the","model",".","Once","the","data","is","parsed",",","use","this","function","to","transform","the","data","into","the","format","your","model","needs",".","Some","example","transformations","can","be",":","-","Converting","to","proto","type","-","Encoding","categorical","features","-","Tokenizing","an","input","sequence","Args",":","data",":","The","previously","extracted","data","from","load_data","Returns",":","Transformed","data",",","in","the","desired","dormat"]
code: def transform_data(self, data):
      """Transforms data into a format that can be directly processed by the model.
  
      Once the data is parsed, use this function to transform the data into the
      format your model needs. Some example transformations can be:
        - Converting to proto type
        - Encoding categorical features
        - Tokenizing an input sequence
  
      Args:
        data: The previously extracted data from load_data
  
      Returns:
        Transformed data, in the desired dormat
      """
      # By default, regurgitates input data if not implemented
      return data
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from abc import ABCMeta
  from abc import abstractmethod
  from multiprocessing import dummy
  import os
  import os.path
  import numpy
  import PIL.Image
  import six
  import tensorflow
label_desc: Use image node_id 4 for calling the DiscreteActivationGeneratorBase obj's underlying member method code with example usage: obj.transform_data(data) and returns: data