code: def testProgramProperties(self):
      def target(x):
          return x
  
      operator = nuts_autobatching.NoUTurnSampler(
          target, step_size=0, use_auto_batching=True
      )
      program = operator.autobatch_context.program_lowered(
          "evolve_trajectory"
      )
  
      def full_var(var):
          return program.var_alloc[var] == inst.VariableAllocation.FULL
  
      # Check that the number of FULL variables doesn't accidentally grow.  This
      # is an equality rather than comparison to remind the maintainer to reduce
      # the expected number when they implement any pass that manages to reduce
      # the count.
      num_full_vars = 0
      for var in program.var_alloc:
          if full_var(var):
              num_full_vars += 1
      self.assertEqual(10, num_full_vars)
  
      # Check that the number of stack pushes doesn't accidentally grow.
      num_full_stack_pushes = 0
      for i in range(program.graph.exit_index()):
          block = program.graph.block(i)
          for op in block.instructions:
              if hasattr(op, "vars_out"):
                  for var in inst.pattern_traverse(op.vars_out):
                      if full_var(var):
                          if (
                              not hasattr(op, "skip_push_mask")
                              or var not in op.skip_push_mask
                          ):
                              num_full_stack_pushes += 1
          if isinstance(block.terminator, inst.PushGotoOp):
              if full_var(inst.pc_var):
                  num_full_stack_pushes += 1
      self.assertEqual(20, num_full_stack_pushes)
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import scale_matvec_tril
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.mcmc import nuts_autobatching
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import sample
label_desc: Use image node_id 17 for calling the NutsTest obj's underlying member method code with example usage: obj.testProgramProperties() and returns: x, unknown