code: def run_functions_eagerly(run_eagerly):
      """Enables / disables eager execution of `tf.function`s.
  
      Calling `tf.config.run_functions_eagerly(True)` will make all
      invocations of `tf.function` run eagerly instead of running as a traced graph
      function. This can be useful for debugging. As the code now runs line-by-line,
      you can add arbitrary `print` messages or pdb breakpoints to monitor the
      inputs/outputs of each Tensorflow operation. However, you should avoid using
      this for actual production because it significantly slows down execution.
  
      >>> def my_func(a):
      ...  print(f'a: {a}')
      ...  return a + a
      >>> a_fn = tf.function(my_func)
  
      >>> # A side effect the first time the function is traced
      >>> # In tracing time, `a` is printed with shape and dtype only
      >>> a_fn(tf.constant(1))
      a: Tensor("a:0", shape=(), dtype=int32)
      <tf.Tensor: shape=(), dtype=int32, numpy=2>
  
      >>> # `print` is a python side effect, it won't execute as the traced function
      >>> # is called
      >>> a_fn(tf.constant(2))
      <tf.Tensor: shape=(), dtype=int32, numpy=4>
  
      >>> # Now, switch to eager running
      >>> tf.config.run_functions_eagerly(True)
      >>> # The code now runs eagerly and the actual value of `a` is printed
      >>> a_fn(tf.constant(2))
      a: 2
      <tf.Tensor: shape=(), dtype=int32, numpy=4>
  
      >>> # Turn this back off
      >>> tf.config.run_functions_eagerly(False)
  
      Note: This flag has no effect on functions passed into tf.data transformations
      as arguments. tf.data functions are never executed eagerly and are always
      executed as a compiled Tensorflow Graph.
  
      Args:
        run_eagerly: Boolean. Whether to run functions eagerly.
      """
      global RUN_FUNCTIONS_EAGERLY
      RUN_FUNCTIONS_EAGERLY = bool(run_eagerly)
  
imports: from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling a global function with example usage: run_functions_eagerly(run_eagerly) without return types