code: def evaluate(step, data, writer, name):
      accuracy_val, summary = sess.run([accuracy, summaries], data)
      writer.add_summary(summary, step)
      writer.flush()
      print("Step %i: %s=%f" % (step, name, accuracy_val))
  
imports: import argparse
  import json
  import tensorflow
  from tensorflow.examples.tutorials.mnist import input_data
label_desc: Use image node_id 15 for calling a global function with example usage: evaluate(step, data, writer, name) without return types