docstr: Compute sigma_t of a given continuous-time label t in [0, T].
docstr_tok: ["Compute","sigma_t","of","a","given","continuous-time","label","t","in","[","0",",","T","]","."]
code: def marginal_std(self, t):
      """
      Compute sigma_t of a given continuous-time label t in [0, T].
      """
      return torch.sqrt(
          1.0 - torch.exp(2.0 * self.marginal_log_mean_coeff(t))
      )
  
imports: import math
  import torch
  from tqdm import tqdm
label_desc: Use image node_id 4 for calling the NoiseScheduleVP obj's underlying member method code with example usage: obj.marginal_std(t) and returns: torch