class_docstr: A bijection of the form,
  
      :math:`\mathbf{y} = \mathbf{L} \mathbf{x} + \mathbf{r}`
  
  where `\mathbf{L}` is a lower triangular matrix and `\mathbf{r}` is a vector.
  
  :param loc: the fixed D-dimensional vector to shift the input by.
  :type loc: torch.tensor
  :param scale_tril: the D x D lower triangular matrix used in the transformation.
  :type scale_tril: torch.tensor
class_docstr_tok: ["A","bijection","of","the","form",",",":","math",":","`","\\mathbf","{","y","}","=","\\mathbf","{","L","}","\\mathbf","{","x","}","+","\\mathbf","{","r","}","`","where","`","\\mathbf","{","L","}","`","is","a","lower","triangular","matrix","and","`","\\mathbf","{","r","}","`","is","a","vector",".",":","param","loc",":","the","fixed","D-dimensional","vector","to","shift","the","input","by",".",":","type","loc",":","torch.tensor",":","param","scale_tril",":","the","D","x","D","lower","triangular","matrix","used","in","the","transformation",".",":","type","scale_tril",":","torch.tensor"]
docstr: Calculates the elementwise determinant of the log Jacobian, i.e.
  log(abs(dy/dx)).
docstr_tok: ["Calculates","the","elementwise","determinant","of","the","log","Jacobian",",","i.e",".","log","(","abs","(","dy\/dx",")",")","."]
code: def log_abs_det_jacobian(self, x, y):
      """
      Calculates the elementwise determinant of the log Jacobian, i.e.
      log(abs(dy/dx)).
      """
      return (
          torch.ones(
              x.size()[:-1],
              dtype=x.dtype,
              layout=x.layout,
              device=x.device,
          )
          * self.scale_tril.diag().log().sum()
      )
  
file_path: pyro/pyro/distributions/transforms/lower_cholesky_affine.py
imports: import torch
  from torch.distributions.transforms import Transform
  from ..None import constraints
  from ..util import copy_docs_from
label_desc: Use image node_id 4 for calling the LowerCholeskyAffine obj's underlying member method code with example usage: obj.log_abs_det_jacobian(x, y) and returns: unknown