code: def get_simple_nested_block_program(opset_version=None):
      @mb.program(
          input_specs=[mb.TensorSpec(shape=(1, 1, 4, 4))],
          opset_version=opset_version,
      )
      def prog(x):
          def true_fn():
              topk, _ = mb.topk(x=x, k=1, axis=-1, ascending=True)
              return mb.add(x=topk, y=1.0)
  
          def false_fn():
              topk, _ = mb.topk(x=x, k=1, axis=-1, ascending=True)
              return mb.add(x=topk, y=2.0)
  
          shape = mb.shape(x=x)
          rank = mb.shape(x=shape)
          pred = mb.squeeze(x=rank)
          return mb.cond(
              pred=mb.cast(x=pred, dtype="bool"),
              _true_fn=true_fn,
              _false_fn=false_fn,
          )
  
      return prog
  
imports: import numpy
  import pytest
  import coremltools
  from coremltools import _logger
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import Function, Program, types
  from coremltools.converters.mil.mil.passes.tests.test_passes import CONSTEXPR_FUNCS
label_desc: Use image node_id 8 for calling a global function with example usage: get_simple_nested_block_program(opset_version) and returns: prog, mb, mb, mb