code: def main(_):
      sess = tf.Session()
  
      # Construct the TensorFlow network.
      n0 = tf.Variable(
          np.ones([FLAGS.tensor_size] * 2),
          dtype=tf.int32,
          name="node_00",
      )
      n1 = tf.Variable(
          np.ones([FLAGS.tensor_size] * 2),
          dtype=tf.int32,
          name="node_01",
      )
  
      for i in range(2, FLAGS.length):
          n0, n1 = n1, tf.add(n0, n1, name="node_%.2d" % i)
  
      sess.run(tf.global_variables_initializer())
  
      # Wrap the TensorFlow Session object for debugging.
      if FLAGS.debug and FLAGS.tensorboard_debug_address:
          raise ValueError(
              "The --debug and --tensorboard_debug_address flags are mutually "
              "exclusive."
          )
      if FLAGS.debug:
          sess = tf_debug.LocalCLIDebugWrapperSession(sess)
  
          def has_negative(_, tensor):
              return np.any(tensor < 0)
  
          sess.add_tensor_filter(
              "has_inf_or_nan", tf_debug.has_inf_or_nan
          )
          sess.add_tensor_filter("has_negative", has_negative)
      elif FLAGS.tensorboard_debug_address:
          sess = tf_debug.TensorBoardDebugWrapperSession(
              sess, FLAGS.tensorboard_debug_address
          )
  
      print(
          "Fibonacci number at position %d:\n%s"
          % (FLAGS.length, sess.run(n1))
      )
  
imports: import argparse
  import sys
  import numpy
  import tensorflow
  from tensorflow.python import debug
label_desc: Use image node_id 1 for calling a global function with example usage: main(_) and returns: np