code: def testCalmerAnf(self):
      # This test has two syntactic features that used to ANF badly:
      # - Literal True `if` argument used to not get replaced
      # - Trying to use a reference in a function call, like `np.array(foo)`, used
      #   to replace `np.array`, causing problems.
      def int_type(args):
          return args[0]
  
      ctx = frontend.Context()
  
      @ctx.batch(type_inference=int_type)
      def function(x):
          # pylint: disable=using-constant-test
          if True:
              return x + np.array(1)
          else:
              return x + np.array(1)
  
      inputs = np.array([1, 5, 60, 3, 7], dtype=np.int32)
      outputs = np.array([2, 6, 61, 4, 8], dtype=np.int32)
      # pylint: disable=unexpected-keyword-arg
      # The `max_stack_depth` and `backend` keyword arguments to `function`
      # are introduced by the `@ctx.batch` decorator, confusing pylint.
      self.assertAllEqual(
          outputs,
          function(inputs, max_stack_depth=3, backend=NP_BACKEND),
      )
  
imports: import collections
  from absl import logging
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.auto_batching import frontend
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.auto_batching import numpy_backend
  from tensorflow_probability.python.experimental.auto_batching import tf_backend
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 23 for calling the AutoGraphFrontendTest obj's underlying member method code with example usage: obj.testCalmerAnf() and returns: args, unknown, unknown