class_docstr: Conditional transforms with learnable parameters such as normalizing flows should inherit from this class rather
  than :class:`~pyro.distributions.conditional.ConditionalTransform` so they are also a subclass of
  :class:`~torch.nn.Module` and inherit all the useful methods of that class.
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
  
imports: from abc import ABC, abstractmethod
  import torch
  import torch.nn
  from .torch import TransformedDistribution
  from .torch_transform import ComposeTransformModule
label_desc: Use image node_id 1 to create a new ConditionalTransformModule object from inherited base classes: ConditionalTransform, torch.nn with example: obj = ConditionalTransformModule()