code: def test_freeze_layerchoice():
      import torch.nn as nn
  
      class Net(ModelSpace):
          def __init__(self):
              super().__init__()
              self.module = LayerChoice(
                  [
                      nn.Conv2d(3, i, kernel_size=1)
                      for i in range(1, 11)
                  ],
                  label="layer",
              )
  
          def forward(self, x):
              return self.module(x)
  
      orig_model = Net()
  
      for i in range(10):
          model = orig_model.freeze({"layer": i})
          inp = torch.randn(1, 3, 3, 3)
          a = getattr(orig_model.module, str(i))(inp)
          b = model(inp)
          assert torch.allclose(a, b)
  
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 26 for calling a global function with example usage: test_freeze_layerchoice() and returns: self