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Create a random variable for Kumaraswamy.


See Kumaraswamy for more details.



Original Docstring for Distribution

Initialize a batch of Kumaraswamy distributions.


  • concentration1: Positive floating-point Tensor indicating mean number of successes; aka 'alpha'. Implies self.dtype and self.batch_shape, i.e., concentration1.shape = [N1, N2, ..., Nm] = self.batch_shape.
  • concentration0: Positive floating-point Tensor indicating mean number of failures; aka 'beta'. Otherwise has same semantics as concentration1.
  • 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.