def topic_log_likelihood(self):
log_likelihood = self._K * numpy.log(self._gamma) - log_factorial(numpy.sum(self._m_k), self._gamma)
for topic_index in xrange(self._K):
log_likelihood += scipy.special.gammaln(self._m_k[topic_index])
log_likelihood += scipy.special.gammaln(self._gamma)
return log_likelihood
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