code: def distribution(
      self,
      distr_args,
      loc: Optional[torch.Tensor] = None,
      scale: Optional[torch.Tensor] = None,
  ) -> PiecewiseLinear:
      if scale is None:
          return self.distr_cls(*distr_args)
      else:
          distr = self.distr_cls(*distr_args)
          return TransformedPiecewiseLinear(
              distr, [AffineTransform(loc=loc, scale=scale)]
          )
  
imports: from typing import Dict, List, Optional, Tuple, cast
  import torch
  import torch.nn.functional
  from torch.distributions import AffineTransform, TransformedDistribution
  from gluonts.core.component import validated
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 3 for calling the PiecewiseLinearOutput obj's underlying member method code with example usage: obj.distribution(distr_args, loc, scale) and returns: self, TransformedPiecewiseLinear