class_docstr: This is the default transform. Using the natural directly saves the forward mode
  gradient, and also gives the analytic optimal solution for gamma=1 in the case
  of Gaussian likelihood.
class_docstr_tok: ["This","is","the","default","transform",".","Using","the","natural","directly","saves","the","forward","mode","gradient",",","and","also","gives","the","analytic","optimal","solution","for","gamma=1","in","the","case","of","Gaussian","likelihood","."]
code: def xi_to_meanvarsqrt(
      xi1: tf.Tensor, xi2: tf.Tensor
  ) -> Tuple[tf.Tensor, tf.Tensor]:
      return natural_to_meanvarsqrt(xi1, xi2)
  
imports: import abc
  import functools
  from typing import Any, Callable, Dict, Optional, Sequence, Tuple, Union
  import tensorflow
  from check_shapes import check_shapes
  from ..base import AnyNDArray, Parameter, _to_constrained
label_desc: Use image node_id 2 for calling the XiNat obj's underlying member method code with example usage: obj.xi_to_meanvarsqrt(xi1, xi2) and returns: natural_to_meanvarsqrt