code: def __init__(self, dim: int = 1) -> None:
      self.dim = dim
      self.args_dim = {k: dim * self.args_dim[k] for k in self.args_dim}
  
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 1 to create a new DistributionOutput object  with example: obj = DistributionOutput(dim)