class_docstr: Create a Dirichlet distribution object.
  
  Parameters
  ----------
  alpha : Tensor or scalar
     Shape parameter of the distribution
class_docstr_tok: ["Create","a","Dirichlet","distribution","object",".","Parameters","--","--","--","--","--","alpha",":","Tensor","or","scalar","Shape","parameter","of","the","distribution"]
code: def entropy(self):
      lgamma = gammaln()
      dgamma = digamma()
      a0 = self.alpha.sum(-1)
      log_B_alpha = lgamma(self.alpha).sum(-1) - lgamma(a0)
      return (
          log_B_alpha
          + (self.alpha - 1).sum(-1) * dgamma(a0)
          - ((self.alpha - 1) * dgamma(self.alpha)).sum(-1)
      )
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/dirichlet.py
imports: from .exp_family import ExponentialFamily
  from .constraint import Positive, Simplex
  from .utils import gammaln, digamma, sample_n_shape_converter, _clip_float_eps
  from ....None import np
label_desc: Use image node_id 7 for calling the Dirichlet obj's underlying member method code with example usage: obj.entropy() and returns: unknown