class_docstr: adapted from https://pytorch.org/tutorials/intermediate/spatial_transformer_tutorial.html
code: def stn(self, x):
      xs = self.localization(x)
      xs = xs.view(-1, 10 * 3 * 3)
      theta = self.fc_loc(xs)
      theta = theta.view(-1, 2, 3)
      x = self.xform(x, theta, spatial_size=x.size()[2:])
      return x
  
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from monai.data import create_test_image_2d
  from monai.networks.layers import AffineTransform
  from monai.utils import set_determinism
  from tests.utils import DistTestCase, TimedCall
label_desc: Use image node_id 3 for calling the STNBenchmark obj's underlying member method code with example usage: obj.stn(x) and returns: x