docstr: Compute alpha_t of a given continuous-time label t in [0, T].
docstr_tok: ["Compute","alpha_t","of","a","given","continuous-time","label","t","in","[","0",",","T","]","."]
code: def marginal_alpha(self, t):
      """
      Compute alpha_t of a given continuous-time label t in [0, T].
      """
      return torch.exp(self.marginal_log_mean_coeff(t))
  
imports: import torch
  import torch.nn.functional
  import math
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling the NoiseScheduleVP obj's underlying member method code with example usage: obj.marginal_alpha(t) and returns: torch