code: def domain_map(  # type: ignore
      cls, df: torch.Tensor, loc: torch.Tensor, scale: torch.Tensor
  ):
      epsilon = torch.finfo(scale.dtype).eps
      scale = F.softplus(scale).clamp_min(epsilon)
      df = 2.0 + F.softplus(df)
      return df.squeeze(-1), loc.squeeze(-1), scale.squeeze(-1)
  
file_path: gluonts/src/gluonts/torch/distributions/studentT.py
imports: from typing import Dict, Tuple, Union
  import torch
  import torch.nn.functional
  from scipy.stats import t
  from torch.distributions import StudentT
  from .distribution_output import DistributionOutput
  from gluonts.util import lazy_property
label_desc: Use image node_id 1 for calling the StudentTOutput obj's underlying member method code with example usage: obj.domain_map(cls, df, loc, scale) and returns: df,  loc,  scale