code: def generator_train():
      inputs = X_train
      targets = y_train
      if len(inputs) != len(targets):
          raise AssertionError(
              "The length of inputs and targets should be equal"
          )
      for _input, _target in zip(inputs, targets):
          # yield _input.encode('utf-8'), _target.encode('utf-8')
          yield _input, _target
  
file_path: TensorLayer/examples/quantized_net/tutorial_binarynet_cifar10_tfrecord.py
imports: import multiprocessing
  import time
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import BinaryConv2d, BinaryDense, Conv2d, Dense, Flatten, Input, LocalResponseNorm, MaxPool2d, Sign
  from tensorlayer.models import Model
label_desc: Use image node_id 2 for calling a global function with example usage: generator_train() without return types