code: def loglike(self):
      neg_evid = -self._sum_by_parts(
          lambda s: (self.nphi[:, s] * self._Elog(s))
      )
  
      prior = torch.as_tensor(self.prior).to(self.nphi)
      K = self.nphi.shape[1]
      log_B_prior = torch.lgamma(prior) * K - torch.lgamma(prior * K)
  
      log_B_posterior = self._sum_by_parts(
          lambda s: torch.lgamma(self._posterior(s))
      ) - torch.lgamma(self.posterior_sum)
  
      return neg_evid - log_B_prior + log_B_posterior
  
imports: import collections
  import functools
  import io
  import os
  import warnings
  import dgl
  import numpy
  import scipy
  import torch
label_desc: Use image node_id 5 for calling the _Dirichlet obj's underlying member method code with example usage: obj.loglike() and returns: unknown