4a28e3ca2c21b48c9b75b99330112d14427b3a6e,GPflow/kernels.py,PeriodicKernel,Kdiag,#PeriodicKernel#Any#,262

Before Change

        self.period = Param(period, transforms.positive)

    def Kdiag(self, X):
        zeros = X[:, 0] * 0
        return zeros + self.variance

    def K(self, X, X2=None):
        X, X2 = self._slice(X, X2)
        if X2 is None:

After Change

        self.period = Param(period, transforms.positive)

    def Kdiag(self, X):
        return tf.fill((tf.shape(X)[0],), self.variance)

    def K(self, X, X2=None):
        X, X2 = self._slice(X, X2)
        if X2 is None:

Instances