LostTech.TensorFlow : API Documentation

Type VectorDeterministic

Namespace tensorflow.contrib.distributions

Parent _BaseDeterministic

Interfaces IVectorDeterministic

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
Show Example
import tensorflow_probability as tfp
            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.]


Public properties

object allow_nan_stats get;

object allow_nan_stats_dyn get;

object atol get;

object atol_dyn get;

TensorShape batch_shape get;

object batch_shape_dyn get;

object dtype get;

object dtype_dyn get;

TensorShape event_shape get;

object event_shape_dyn get;

object loc get;

object loc_dyn get;

string name get;

object name_dyn get;

IDictionary<object, object> parameters get;

object parameters_dyn get;

object PythonObject get;

object reparameterization_type get;

object reparameterization_type_dyn get;

object rtol get;

object rtol_dyn get;

object validate_args get;

object validate_args_dyn get;