code: def test_solver_order_and_type(self):
      for algorithm_type in [
          "dpmsolver",
          "dpmsolver++",
          "sde-dpmsolver",
          "sde-dpmsolver++",
      ]:
          for solver_type in ["midpoint", "heun"]:
              for order in [1, 2, 3]:
                  for prediction_type in ["epsilon", "sample"]:
                      if algorithm_type in [
                          "sde-dpmsolver",
                          "sde-dpmsolver++",
                      ]:
                          if order == 3:
                              continue
                      else:
                          self.check_over_configs(
                              solver_order=order,
                              solver_type=solver_type,
                              prediction_type=prediction_type,
                              algorithm_type=algorithm_type,
                          )
                      sample = self.full_loop(
                          solver_order=order,
                          solver_type=solver_type,
                          prediction_type=prediction_type,
                          algorithm_type=algorithm_type,
                      )
                      assert not torch.isnan(
                          sample
                      ).any(), "Samples have nan numbers"
  
imports: import tempfile
  import torch
  from diffusers import DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 10 for calling the DPMSolverMultistepSchedulerTest obj's underlying member method code with example usage: obj.test_solver_order_and_type() without return types