Type Gumbel
Namespace tensorflow.contrib.distributions.bijectors
Parent Bijector
Interfaces IGumbel
Compute `Y = g(X) = exp(-exp(-(X - loc) / scale))`. This bijector maps inputs from `[-inf, inf]` to [0, 1]`. The inverse of the
bijector applied to a uniform random variable `X ~ U(0, 1) gives back a
random variable with the
[Gumbel distribution](https://en.wikipedia.org/wiki/Gumbel_distribution): ```none
Y ~ Gumbel(loc, scale)
pdf(y; loc, scale) = exp(
-( (y - loc) / scale + exp(- (y - loc) / scale) ) ) / scale
```
Properties
Public properties
object dtype get;
object dtype_dyn get;
object forward_min_event_ndims get;
object forward_min_event_ndims_dyn get;
IList<object> graph_parents get;
object graph_parents_dyn get;
object inverse_min_event_ndims get;
object inverse_min_event_ndims_dyn get;
bool is_constant_jacobian get;
object is_constant_jacobian_dyn get;
Tensor loc get;
The `loc` in `Y = g(X) = exp(-exp(-(X - loc) / scale))`.
object loc_dyn get;
The `loc` in `Y = g(X) = exp(-exp(-(X - loc) / scale))`.
object name get;
object name_dyn get;
object PythonObject get;
object scale get;
This is `scale` in `Y = g(X) = exp(-exp(-(X - loc) / scale))`.
object scale_dyn get;
This is `scale` in `Y = g(X) = exp(-exp(-(X - loc) / scale))`.