"""
Test the losses layers
"""
import numpy as np
from n3fit.layers import losses
from .test_backend import are_equal, DIM
ARR1 = np.random.rand(DIM)
ARR2 = np.random.rand(DIM)
C = np.random.rand(DIM, DIM)
INVCOVMAT = np.linalg.inv(C @ C.T)
# Tests loss functions
[docs]def test_l_invcovmat():
loss_f = losses.LossInvcovmat(INVCOVMAT, ARR1)
# Add a replica and batch dimension to T2
result = loss_f(np.expand_dims(ARR2, [0, 1]))
y = ARR1 - ARR2
tmp = np.dot(INVCOVMAT, y)
reference = np.dot(y, tmp)
are_equal(result, reference, threshold=1e-4)
[docs]def test_l_positivity():
alpha = 1e-7
loss_f = losses.LossPositivity(alpha=alpha)
result = loss_f(np.expand_dims(ARR2, [0, 1]))
def elu_sum(yarr_in):
"""Applies Exponential Linear Unit
to an array and sums it up"""
yarr = -yarr_in
res = 0.0
for y in yarr:
if y > 0:
res += y
else:
res += alpha * (np.exp(y) - 1)
return res
reference = elu_sum(ARR1)
are_equal(result, reference)