Create a random variable for GeneralizedNormal.

See GeneralizedNormal for more details.


Original Docstring for Distribution

Construct Generalized Normal distributions.

The Generalized Normal is parametrized with mean loc, scale scale and shape parameter power. The parameters must be shaped in a way that supports broadcasting (e.g. loc + scale is a valid operation).

loc Floating point tensor; the means of the distribution(s).
scale Floating point tensor; the scale of the distribution(s). Must contain only positive values.
power Floating point tensor; the shape parameter of the distribution(s). Must contain only positive values. loc, scale and power must have compatible shapes for broadcasting.
validate_args Python bool, default False. When True distribution parameters are checked for validity despite possibly degrading runtime performance. When False invalid inputs may silently render incorrect outputs.
allow_nan_stats Python bool, default True. When True, statistics (e.g., mean, mode, variance) use the value "NaN" to indicate the result is undefined. When False, an exception is raised if one or more of the statistic's batch members are undefined.
name Python str name prefixed to Ops created by this class.

TypeError if loc, scale, and power have different dtype.