code: def test_reinforcement_learning(self):
      class Policy(nn.Module):
          def __init__(self):
              super(Policy, self).__init__()
              self.affine1 = nn.Linear(4, 128)
              self.affine2 = nn.Linear(128, 2)
  
          def forward(self, x):
              x = F.relu(self.affine1(x))
              action_scores = self.affine2(x)
              return F.softmax(action_scores, dim=1)
  
      self.checkExportImport(Policy(), (torch.rand(1, 4),))
  
imports: import unittest
  import torch
  import torch.nn.functional
  import torchvision
  import nni.nas.nn.pytorch.layers
  from nni.nas.nn.pytorch import ParametrizedModule
  from .convert_mixin import ConvertMixin, ConvertWithShapeMixin
label_desc: Use image node_id 4 for calling the TestConvert obj's underlying member method code with example usage: obj.test_reinforcement_learning() and returns: F