class_docstr: Implements a location-scale heavy-tail Lambert W x Normal distribution.
class_docstr_tok: ["Implements","a","location-scale","heavy-tail","Lambert","W","x","Normal","distribution","."]
docstr: Location parameter of the Lambert W x Normal distribution.
docstr_tok: ["Location","parameter","of","the","Lambert","W","x","Normal","distribution","."]
code: def loc(self):
      """Location parameter of the Lambert W x Normal distribution."""
      return self._loc
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import lambertw_transform
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
label_desc: Use image node_id 2 for calling the LambertWNormal obj's underlying member method code with example usage: obj.loc() and returns: self