class_docstr: Dirichlet-Multinomial distribution, specified by the concentration vector
  alpha of length dim, and a number of trials n_trials.
  https://en.wikipedia.org/wiki/Dirichlet-multinomial_distribution
  
  The Dirichlet-Multinomial distribution is a discrete multivariate
  probability distribution, a sample (or observation)
  x = (x_0,..., x_{dim-1}) must satisfy:
  
  sum_k x_k = n_trials and for all k, x_k is a non-negative integer.
  
  Such a sample can be obtained by first drawing a vector p from a
  Dirichlet(alpha) distribution, then x is drawn from a Multinomial(p) with n
  trials.
  
  Parameters
  ----------
  dim
      Dimension of any sample
  
  n_trials
      Number of trials
  
  alpha
      concentration vector, of shape (..., dim)
  
  F
      A module that can either refer to the Symbol API or the NDArray
      API in MXNet
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code: def F(self):
      return getF(self.alpha)
  
imports: from typing import Optional, Tuple, Type
  import numpy
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.util import make_nd_diag
  from .distribution import Distribution, _sample_multiple, getF
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 2 for calling the DirichletMultinomial obj's underlying member method code with example usage: obj.F() and returns: getF