code: def _marginal_std(self, t: Tensor) -> Tensor:
      return torch.sqrt(
          1.0 - torch.exp(2.0 * self._marginal_log_mean_coef(t))
      )
  
imports: import math
  import torch
  from torch import Tensor
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Optional
  from .ddim import DDIMQSampler
  from .basic import merge_ref
  from .utils import append_dims
  from .utils import interpolate_fn
  from .schema import ISampler
  from .schema import IQSampler
  from .schema import IDiffusion
  from .schema import UncondSamplerMixin
  from ..utils import cond_type
  from .....misc.toolkit import get_device
label_desc: Use image node_id 16 for calling the DPMSolver obj's underlying member method code with example usage: obj._marginal_std(t) and returns: torch