class_docstr: Negative Binomial distribution output class.
code: def distribution(
      self,
      distr_args,
      loc: Optional[torch.Tensor] = None,
      scale: Optional[torch.Tensor] = None,
  ) -> Distribution:
      total_count, logits = distr_args
  
      if scale is not None:
          # See scaling property of Gamma.
          logits += scale.log()
  
      return self._base_distribution((total_count, logits))
  
imports: from typing import Callable, Dict, Optional, Tuple
  import torch
  from torch import nn
  from torch.distributions import AffineTransform, Distribution, Independent, NegativeBinomial, Normal, StudentT, TransformedDistribution
label_desc: Use image node_id 3 for calling the NegativeBinomialOutput obj's underlying member method code with example usage: obj.distribution(distr_args, loc, scale) and returns: self