code: def set_synchronous_execution(enable):
      """Specifies whether operations are executed synchronously or asynchronously.
  
      TensorFlow can execute operations synchronously or asynchronously. If
      asynchronous execution is enabled, operations may return "non-ready" handles.
  
      When `enable` is set to None, an appropriate value will be picked
      automatically. The value picked may change between TensorFlow releases.
  
      Args:
        enable: Whether operations should be dispatched synchronously.
          Valid values:
          - None: sets the system default.
          - True: executes each operation synchronously.
          - False: executes each operation asynchronously.
      """
      if enable is None:
          context.context().execution_mode = None
      elif enable:
          context.context().execution_mode = context.SYNC
      else:
          context.context().execution_mode = context.ASYNC
  
imports: from typing import Union
  from tensorflow.python.eager import context
  from tensorflow.python.framework import errors
  from tensorflow.python.util import _pywrap_determinism
  from tensorflow.python.util import _pywrap_tensor_float_32_execution
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 16 for calling a global function with example usage: set_synchronous_execution(enable) without return types