import tensorflow as tf

# This file was modified by Vincent ADAM
# ------------------------------------------

import tensorflow as tf
from settings import float_type
from quadrature import hermgauss
import numpy as np


def eye(N):
    """
    An identitiy matrix
    """
    return tf.diag(tf.ones(tf.stack([N, ]), dtype=float_type))


def variational_expectations( Fmu, Fvar, phi, num_gauss_hermite_points=20):
    """
    Compute the expected value of a function phi, given a Gaussian
    distribution for the input values.
    if
        q(f) = N(Fmu, Fvar)
    then this method computes
       \int phi(f) q(f) df.
    Here, we implement a default Gauss-Hermite quadrature routine
    """
