class_docstr: Test case for the optim module.
code: def _run_correctness_test(self, opt, model, override=None):
      for i in range(10):
          fmodel = higher.patch.monkeypatch(model)
          diffopt = higher.optim.get_diff_optim(
              opt, model.parameters(), fmodel, override=override
          )
          for j in range(3):
              opt.zero_grad()
              x = torch.rand(10, 4)
  
              y_model = model(x)
              y_fmodel = fmodel(x)
  
              loss_model = y_model.pow(2).sum()
              loss_fmodel = y_fmodel.pow(2).sum()
  
              loss_model.backward()
              diffopt.step(loss_fmodel)
              opt.step()
              self.assertEqual(
                  len(list(model.parameters())),
                  len(list(fmodel.parameters())),
              )
  
          for p, fp in zip(model.parameters(), fmodel.parameters()):
              torch.testing.assert_allclose(p, fp, atol=1e-5, rtol=1e-1)
  
imports: import unittest
  import copy
  from parameterized import parameterized
  import torch
  from torch import nn, optim
  import higher
label_desc: Use image node_id 4 for calling the TestOptim obj's underlying member method code with example usage: obj._run_correctness_test(opt, model, override) without return types