docstr: Singlestep DPM-Solver with the order `order` from time `s` to time `t`.
  Args:
      x: A pytorch tensor. The initial value at time `s`.
      s: A pytorch tensor. The starting time, with the shape (x.shape[0],).
      t: A pytorch tensor. The ending time, with the shape (x.shape[0],).
      order: A `int`. The order of DPM-Solver. We only support order == 1 or 2 or 3.
      return_intermediate: A `bool`. If true, also return the model value at time `s`, `s1` and `s2` (the intermediate times).
      solver_type: either 'dpm_solver' or 'taylor'. The type for the high-order solvers.
          The type slightly impacts the performance. We recommend to use 'dpm_solver' type.
      r1: A `float`. The hyperparameter of the second-order or third-order solver.
      r2: A `float`. The hyperparameter of the third-order solver.
  Returns:
      x_t: A pytorch tensor. The approximated solution at time `t`.
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code: def singlestep_dpm_solver_update(
      self,
      x,
      s,
      t,
      order,
      return_intermediate=False,
      solver_type="dpm_solver",
      r1=None,
      r2=None,
  ):
      """
      Singlestep DPM-Solver with the order `order` from time `s` to time `t`.
      Args:
          x: A pytorch tensor. The initial value at time `s`.
          s: A pytorch tensor. The starting time, with the shape (x.shape[0],).
          t: A pytorch tensor. The ending time, with the shape (x.shape[0],).
          order: A `int`. The order of DPM-Solver. We only support order == 1 or 2 or 3.
          return_intermediate: A `bool`. If true, also return the model value at time `s`, `s1` and `s2` (the intermediate times).
          solver_type: either 'dpm_solver' or 'taylor'. The type for the high-order solvers.
              The type slightly impacts the performance. We recommend to use 'dpm_solver' type.
          r1: A `float`. The hyperparameter of the second-order or third-order solver.
          r2: A `float`. The hyperparameter of the third-order solver.
      Returns:
          x_t: A pytorch tensor. The approximated solution at time `t`.
      """
      if order == 1:
          return self.dpm_solver_first_update(
              x, s, t, return_intermediate=return_intermediate
          )
      elif order == 2:
          return self.singlestep_dpm_solver_second_update(
              x,
              s,
              t,
              return_intermediate=return_intermediate,
              solver_type=solver_type,
              r1=r1,
          )
      elif order == 3:
          return self.singlestep_dpm_solver_third_update(
              x,
              s,
              t,
              return_intermediate=return_intermediate,
              solver_type=solver_type,
              r1=r1,
              r2=r2,
          )
      else:
          raise ValueError(
              "Solver order must be 1 or 2 or 3, got {}".format(order)
          )
  
imports: import torch
  import torch.nn.functional
  import math
  from tqdm import tqdm
label_desc: Use image node_id 13 for calling the DPM_Solver obj's underlying member method code with example usage: obj.singlestep_dpm_solver_update(x, s, t, order, return_intermediate, solver_type, r1, r2) and returns: self, self, self