docstr: Calculates the natural gradient with respect to nat_mean, nat_covar
docstr_tok: ["Calculates","the","natural","gradient","with","respect","to","nat_mean",",","nat_covar"]
code: def backward(ctx, dout_dmu, dout_dL):
      "Calculates the natural gradient with respect to nat_mean, nat_covar"
      mu, L = ctx.saved_tensors
      C = _triangular_inverse(L, upper=False)
      return _NaturalToMuVarSqrt._backward(dout_dmu, dout_dL, mu, L, C)
  
imports: import abc
  import torch
  from linear_operator.operators import CholLinearOperator, TriangularLinearOperator
  from linear_operator.utils.cholesky import psd_safe_cholesky
  from ..distributions import MultivariateNormal
  from ._variational_distribution import _VariationalDistribution
label_desc: Use image node_id 4 for calling the _NaturalToMuVarSqrt obj's underlying member method code with example usage: obj.backward(ctx, dout_dmu, dout_dL) and returns: _NaturalToMuVarSqrt