code: def load_AE(codec_prefix, print_summary=False):
      saveFilePrefix = "models/AE_codec/" + codec_prefix + "_"
  
      decoder_model_filename = saveFilePrefix + "decoder.json"
      decoder_weight_filename = saveFilePrefix + "decoder.h5"
  
      if not os.path.isfile(decoder_model_filename):
          raise Exception(
              "The file for decoder model does not exist:{}".format(
                  decoder_model_filename
              )
          )
      json_file = open(decoder_model_filename, "r")
      decoder = model_from_json(
          json_file.read(), custom_objects={"tf": tf}
      )
      json_file.close()
  
      if not os.path.isfile(decoder_weight_filename):
          raise Exception(
              "The file for decoder weights does not exist:{}".format(
                  decoder_weight_filename
              )
          )
      decoder.load_weights(decoder_weight_filename)
  
      if print_summary:
          print("Decoder summaries")
          decoder.summary()
  
      return decoder
  
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 1 for calling a global function with example usage: load_AE(codec_prefix, print_summary) and returns: decoder