(self, Xnew, full_cov=False)
return self.output_transform.build_backward(f), self.output_transform.build_backward_variance(var)
build_predict builds the TensorFlow graph for prediction. Similar to the method in the wrapped model, however
        the input points are transformed using the input transform. The returned mean and variance are transformed
        backward using the output transform.
build_predict builds the TensorFlow graph for prediction. Similar to the method in the wrapped model, however
        the input points are transformed using the input transform. The returned mean and variance are transformed
        backward using the output transform.
build_predict builds the TensorFlow graph for prediction . Similar to the method in the wrapped model however the input points are transformed using the input transform . The returned mean and variance are transformed backward using the output transform .
def build_predict(self, Xnew, full_cov=False):
        """
        build_predict builds the TensorFlow graph for prediction. Similar to the method in the wrapped model, however
        the input points are transformed using the input transform. The returned mean and variance are transformed
        backward using the output transform.
        """
        f, var = self.wrapped.build_predict(self.input_transform.build_forward(Xnew), full_cov=full_cov)
        return self.output_transform.build_backward(f), self.output_transform.build_backward_variance(var)
def build_predict ( self , Xnew , full_cov = False ) : f , var = self . wrapped . build_predict ( self . input_transform . build_forward ( Xnew ) , full_cov = full_cov ) return self . output_transform . build_backward ( f ) , self . output_transform . build_backward_variance ( var )