code: def build_validation(x, y_):
      net = model(x, is_train=False)
      cost = tl.cost.cross_entropy(net.outputs, y_, name="cost_test")
      accurate_prediction = tf.equal(tf.argmax(net.outputs, 1), y_)
      accuracy = tf.reduce_mean(
          tf.cast(accurate_prediction, tf.float32), name="accuracy_test"
      )
      return net, [cost, accuracy]
  
file_path: TensorLayer/examples/distributed_training/tutorial_cifar10_distributed_trainer.py
imports: import multiprocessing
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import BatchNormLayer, Conv2d, DenseLayer, FlattenLayer, InputLayer, MaxPool2d
label_desc: Use image node_id 6 for calling a global function with example usage: build_validation(x, y_) and returns: net,  list