class_docstr: Base class for Deterministic distributions.
class_docstr_tok: ["Base","class","for","Deterministic","distributions","."]
docstr: Point (or batch of points) at which this distribution is supported.
docstr_tok: ["Point","(","or","batch","of","points",")","at","which","this","distribution","is","supported","."]
code: def loc(self):
      """Point (or batch of points) at which this distribution is supported."""
      return self._loc
  
imports: import abc
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import pad
  from tensorflow_probability.python.bijectors import reshape
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 3 for calling the _BaseDeterministic obj's underlying member method code with example usage: obj.loc() and returns: self