code: def get_scheduler_config(self, **kwargs):
      config = {
          "num_train_timesteps": 1000,
          "beta_start": 0.0001,
          "beta_end": 0.02,
          "beta_schedule": "linear",
          "solver_order": 2,
          "prediction_type": "epsilon",
          "thresholding": False,
          "sample_max_value": 1.0,
          "algorithm_type": "dpmsolver++",
          "solver_type": "midpoint",
          "lower_order_final": False,
          "euler_at_final": False,
          "lambda_min_clipped": -float("inf"),
          "variance_type": None,
      }
  
      config.update(**kwargs)
      return config
  
imports: import tempfile
  import torch
  from diffusers import DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 1 for calling the DPMSolverMultistepSchedulerTest obj's underlying member method code with example usage: obj.get_scheduler_config() and returns: config