code: def predict(self, data):
      # this is used inside tf session, data should be a tensor
      return self.model(data)
  
file_path: AIX360/aix360/algorithms/contrastive/CEM_MAF_utils.py
imports: import tensorflow
  import os
  import numpy
  import scipy.misc
  from tensorflow.contrib.keras.api.keras.applications.resnet50 import ResNet50
  from tensorflow.contrib.keras.api.keras.applications.vgg16 import VGG16
  from tensorflow.contrib.keras.api.keras.layers import Input, Dense, Dropout, LeakyReLU, Activation
  from tensorflow.contrib.keras.api.keras.models import Model, model_from_json, Sequential
  from tensorflow.contrib.keras.api.keras.callbacks import ModelCheckpoint
  from tensorflow.contrib.keras.api.keras import metrics
  from tensorflow.contrib.keras.api.keras import regularizers
  from tensorflow.contrib.keras.api.keras.optimizers import SGD
label_desc: Use image node_id 2 for calling the CELEBAModel obj's underlying member method code with example usage: obj.predict(data) and returns: self