code: def test_value_choice_in_functional(
      space_format: Type[ExecutableModelSpace], nn: ModuleType
  ):
      # We no longer support this.
      # Testing it to make sure it raises an error.
  
      class Net(ModelSpace, label_prefix="model"):
          def __init__(self):
              super().__init__()
              self.dropout_rate = Categorical([0.0, 1.0])
  
          def forward(self, x):
              return F.dropout(x, self.dropout_rate())
  
      if issubclass(space_format, GraphModelSpace):
          with pytest.raises(RuntimeError, match="TorchScript"):
              model = space_format.from_model(Net())
      else:
          model = space_format.from_model(Net())
          assert len(model.simplify()) == 0
          with pytest.raises(TypeError, match="not callable"):
              model.freeze({}).executable_model()(
                  torch.randn(1, 3, 3, 3)
              )
  
imports: import copy
  import random
  from types import ModuleType
  from typing import Type
  import pytest
  import nni
  import nni.nas.nn.pytorch.layers
  import nni.nas.evaluator.pytorch.lightning
  import torch
  import torch.nn.functional
  from nni.mutable import Categorical, ensure_frozen, label_scope, SampleValidationError
  from nni.nas.evaluator import FunctionalEvaluator
  from nni.nas.space import RawFormatModelSpace, SimplifiedModelSpace, ExecutableModelSpace, GraphModelSpace, model_context
  from nni.nas.space.pytorch import PytorchGraphModelSpace
  from nni.nas.nn.pytorch import ParametrizedModule, MutableModule, ModelSpace, LayerChoice, InputChoice, Cell, ChosenInputs, MutableConv2d, MutableLinear
label_desc: Use image node_id 15 for calling a global function with example usage: test_value_choice_in_functional(space_format, nn) and returns: F