class_docstr: Create a Beta distribution object.
  
  Parameters
  ----------
  alpha : Tensor or scalar
     The first shape parameter
  beta : Tensor or scalar
      The second shape parameter
class_docstr_tok: ["Create","a","Beta","distribution","object",".","Parameters","--","--","--","--","--","alpha",":","Tensor","or","scalar","The","first","shape","parameter","beta",":","Tensor","or","scalar","The","second","shape","parameter"]
code: def __init__(self, alpha, beta, validate_args=None):
      self.alpha = alpha
      self.beta = beta
      super(Beta, self).__init__(
          event_dim=0, validate_args=validate_args
      )
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/beta.py
imports: from .exp_family import ExponentialFamily
  from .constraint import UnitInterval, Positive
  from .utils import sample_n_shape_converter, gammaln, digamma, _clip_prob
  from ....None import np
label_desc: Use image node_id 1 to create a new Beta object from inherited base classes: ExponentialFamily with example: obj = Beta(alpha, beta, validate_args)