516f97c543f0816677fd00ec24b47f31f2618f67,gpflow/models/sgpr.py,SGPR,log_likelihood,#SGPR#,149

Before Change

        X_data, Y_data = self.data

        num_inducing = len(self.inducing_variable)
        num_data = tf.cast(tf.shape(Y_data)[0], default_float())
        output_dim = tf.cast(tf.shape(Y_data)[1], default_float())

        err = Y_data - self.mean_function(X_data)
        Kdiag = self.kernel(X_data, full_cov=False)
        kuf = Kuf(self.inducing_variable, self.kernel, X_data)

After Change

        X_data, Y_data = self.data

        num_inducing = len(self.inducing_variable)
        num_data = to_default_float(tf.shape(Y_data)[0])
        output_dim = to_default_float(tf.shape(Y_data)[1])

        err = Y_data - self.mean_function(X_data)
        Kdiag = self.kernel(X_data, full_cov=False)

Instances