0b169fcf6e089ad7e6c9a8faf3aaf69de28ebef5,pymc3/distributions/multivariate.py,MvNormal,logp,#MvNormal#Any#,190

Before Change

        delta = value - mu

        if self._cov_type == "cov":
            // Use this when Theano/񴌄 is released.
            // return MvNormalLogp()(self.cov, delta)
            logp = self._logp_cov(delta)
        elif self._cov_type == "tau":
            logp = self._logp_tau(delta)
        else:
            logp = self._logp_chol(delta)

        if onedim:
            return logp[0]
        return logp

    def _logp_chol(self, delta):
        chol_cov = self.chol_cov

After Change

    def logp(self, value):
        quaddist, logdet, ok = self._quaddist(value)
        k = value.shape[-1].astype(theano.config.floatX)
        norm = - 0.5 * k * pm.floatX(np.log(2 * np.pi))
        return bound(norm - 0.5 * quaddist - logdet, ok)

    def _repr_latex_(self, name=None, dist=None):
        if dist is None:
            dist = self

Instances