class_docstr: Dirichlet Distribution.
  
  The probability density function of the distribution is expressed as
  
  .. math::
      p(x) = \frac{\Gamma(\sum_{i=1}^{K} \alpha_i)}
          {\prod_{i=1}^{K} \Gamma (\alpha_i)}
          \prod_{i=1}^{K} {x_i}^{\alpha_i-1}
  
  Args:
      alpha(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution.
code: def event_shape(self):
      return self.alpha.shape[-1:]
  
imports: import numpy
  import chainer
  from chainer import distribution
  from chainer.functions.array import expand_dims
  from chainer.functions.math import digamma
  from chainer.functions.math import exponential
  from chainer.functions.math import lgamma
  from chainer.functions.math import sum
  from chainer.utils import cache
label_desc: Use image node_id 6 for calling the Dirichlet obj's underlying member method code with example usage: obj.event_shape() and returns: self