code: def test_nested_transform_with(
      self,
      transform_fn=None,
      mlir_pipeline=None,
      nested_fn=False,
      nested_mlir=False,
  ):
      @def_function.function
      def f(x, y, z):
          @def_function.function
          def inner_add():
              return math_ops.add(y, z, name="x_plus_y")
  
          return math_ops.add(x, inner_add(), name="x_plus_y")
  
      # 1, 2, 4 are picked so the following combinations create different results.
      # 1 + (2 + 4) = 7
      # 1 + (2 * 4) = 9
      # 1 * (2 + 4) = 6
      # 1 * (2 * 4) = 8
      inputs = [1.0, 2.0, 4.0]
      self.assertEqual(f(*inputs), 7.0)  # 1 + (2 + 4) = 7
  
      # Extract all the functions in `f`'s library that we want to transform.
      nested_fn_transforms = {}
      nested_mlir_transforms = {}
  
      cf = f.get_concrete_function(*inputs)
      gdef = cf.graph.as_graph_def()
      for fdef in gdef.library.function:
          fdef_name = fdef.signature.name
          if nested_fn:
              nested_fn_transforms[fdef_name] = add_to_multiply
          if nested_mlir:
              nested_mlir_transforms[fdef_name] = "test-pass"
  
      # Transform `f` and all of its library functions.
      updated_f = transform.transform_function(
          f,
          inputs=inputs,
          transform_fn=transform_fn,
          mlir_pipeline=mlir_pipeline,
          nested_fn_transforms=nested_fn_transforms,
          nested_mlir_transforms=nested_mlir_transforms,
      )
      self.assertEqual(updated_f(*inputs), 8.0)
  
imports: import collections
  from absl.testing import parameterized
  from tensorflow.core.function.testing import test_pass
  from tensorflow.core.function.transform import transform
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.module import module
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import load
  from tensorflow.python.saved_model import save
label_desc: Use image node_id 8 for calling the TransformTest obj's underlying member method code with example usage: obj.test_nested_transform_with(transform_fn, mlir_pipeline, nested_fn, nested_mlir) and returns: math_ops, math_ops