code: def create_reader(path, is_training, input_dim, label_dim):
      deserializer = C.io.CTFDeserializer(
          filename=path,
          streams=C.io.StreamDefs(
              labels_unused=C.io.StreamDef(
                  field="labels", shape=label_dim, is_sparse=False
              ),
              features=C.io.StreamDef(
                  field="features", shape=input_dim, is_sparse=False
              ),
          ),
      )
      return C.io.MinibatchSource(
          deserializers=deserializer,
          randomize=is_training,
          max_sweeps=C.io.INFINITELY_REPEAT if is_training else 1,
      )
  
file_path: CNTK/Examples/Image/GAN/Basic_GAN_Distributed.py
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import os
  import argparse
  import cntk
  import cntk.tests.test_utils
  from timeit import default_timer
label_desc: Use image node_id 1 for calling a global function with example usage: create_reader(path, is_training, input_dim, label_dim) and returns: C