import tensorflow as tf

      tf.float32, # data_type for input fed to the graph
      train=False, # doing inference
      resize_method='crop')
  images, labels = preprocessor.minibatch(dataset, subset='train')
  graph = load_graph(model_file)
  input_tensor = graph.get_tensor_by_name(input_layer + ":0")
  output_tensor = graph.get_tensor_by_name(output_layer + ":0")
  
  config = tf.compat.v1.ConfigProto()
  config.inter_op_parallelism_threads = num_inter_threads
  config.intra_op_parallelism_threads = num_intra_threads

  total_accuracy1, total_accuracy5 = (0.0, 0.0)
  num_processed_images = 0
  num_remaining_images = 5000
  top1 = 0
