code: def test_mapper(self):
      _ = torch.manual_seed(0)
      dist = DistributionWithMapper(
          Normal(0.0, 1.0), map_fn=nn.Sigmoid()
      )
      out = dist.rsample((8,))
      exp = torch.tensor(
          [
              0.8236,
              0.4272,
              0.1017,
              0.6384,
              0.2527,
              0.1980,
              0.5995,
              0.6980,
          ]
      )
      assert_close(out, exp, rtol=1e-4, atol=1e-4)
  
imports: import torch
  from torch import nn
  from torch.distributions import Normal
  from kornia.augmentation.random_generator import DistributionWithMapper
  from kornia.testing import assert_close
label_desc: Use image node_id 1 for calling the TestDistMapper obj's underlying member method code with example usage: obj.test_mapper() without return types