class_docstr: Vector `Deterministic` distribution on `R^k`.
  
  The `VectorDeterministic` distribution is parameterized by a [batch] point
  `loc in R^k`.  The distribution is supported at this point only,
  and corresponds to a random variable that is constant, equal to `loc`.
  
  See [Degenerate rv](https://en.wikipedia.org/wiki/Degenerate_distribution).
  
  #### Mathematical Details
  
  The probability mass function (pmf) is
  
  ```none
  pmf(x; loc)
    = 1, if All[Abs(x - loc) <= atol + rtol * Abs(loc)],
    = 0, otherwise.
  ```
  
  #### Examples
  
  ```python
  tfd = tfp.distributions
  
  # Initialize a single VectorDeterministic supported at [0., 2.] in R^2.
  constant = tfd.Deterministic([0., 2.])
  constant.prob([0., 2.])
  ==> 1.
  constant.prob([0., 3.])
  ==> 0.
  
  # Initialize a [3] batch of constants on R^2.
  loc = [[0., 1.], [2., 3.], [4., 5.]]
  constant = tfd.VectorDeterministic(loc)
  constant.prob([[0., 1.], [1.9, 3.], [3.99, 5.]])
  ==> [1., 0., 0.]
  ```
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code: def _event_shape(self):
      return self.loc.shape[-1:]
  
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 4 for calling the VectorDeterministic obj's underlying member method code with example usage: obj._event_shape() and returns: self