code: def synthetic_pattern_program():
      """A program that tests pattern matching of `PrimOp` outputs.
  
      Returns:
        program: `instructions.Program`.
      """
      block = instructions.Block(
          [
              instructions.prim_op(
                  [], ("one", ("five", "three")), lambda: (1, (2, 3))
              ),
              instructions.prim_op(
                  [], (("four", "five"), "six"), lambda: ((4, 5), 6)
              ),
          ],
          instructions.halt_op(),
      )
  
      the_vars = {
          "one": instructions.single_type(np.int64, ()),
          "three": instructions.single_type(np.int64, ()),
          "four": instructions.single_type(np.int64, ()),
          "five": instructions.single_type(np.int64, ()),
          "six": instructions.single_type(np.int64, ()),
      }
  
      return instructions.Program(
          instructions.ControlFlowGraph([block]),
          [],
          the_vars,
          [],
          (("one", "three"), "four", ("five", "six")),
      )
  
file_path: probability/tensorflow_probability/python/experimental/auto_batching/test_programs.py
imports: import numpy
  from tensorflow_probability.python.experimental.auto_batching import instructions
label_desc: Use image node_id 4 for calling a global function with example usage: synthetic_pattern_program() and returns: instructions