code: def __init__(self, permutation=None, LU=None):
      super(ConditionedGeneralizedChannelPermute, self).__init__(
          cache_size=1
      )
  
      self.permutation = permutation
      self.LU = LU
  
imports: import torch
  from torch.distributions import Transform
  from pyro.nn import DenseNN
  from ..None import constraints
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 1 to create a new ConditionedGeneralizedChannelPermute object from inherited base classes: Transform with example: obj = ConditionedGeneralizedChannelPermute(permutation, LU)