class_docstr: self = TestOptimize()
  self.setUp()
code: def test_optimize(self):
      # TODO: Add tests for other optimizers
      for opt in [
          "adadelta",
          "adam",
          "adamax",
          "asgd",
          "lbfgs",
          "rmsprop",
          "rprop",
      ]:
          A = torch.randn(
              5,
              5,
              device=config.DEVICE,
              dtype=config.DTYPE,
              requires_grad=True,
          )
          B = torch.ones(
              5,
              5,
              device=config.DEVICE,
              dtype=config.DTYPE,
              requires_grad=False,
          )
          params = optimize(
              self.loss_fn,
              params={"A": A},
              loss_args={"B": B},
              opt=opt,
              max_iter=int(1e6),
          )
  
          npt.assert_almost_equal(
              B.data.cpu().numpy(),
              params["A"].detach().cpu().numpy().round(),
              decimal=1,
          )
  
file_path: pgmpy/pgmpy/tests/test_utils/test_optimizer.py
imports: import unittest
  import numpy
  import numpy.testing
  import torch
  from pgmpy import config
  from pgmpy.utils import optimize, pinverse
label_desc: Use image node_id 3 for calling the TestOptimize obj's underlying member method code with example usage: obj.test_optimize() without return types