code: def L(self):
      return self.LU.tril(diagonal=-1) + torch.eye(
          self.LU.size(-1), dtype=self.LU.dtype, device=self.LU.device
      )
  
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 3 for calling the ConditionedGeneralizedChannelPermute obj's underlying member method code with example usage: obj.L() and returns: unknown