``````# Copyright 2017 the GPflow authors.
#
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#
# Unless required by applicable law or agreed to in writing, software
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and

import tensorflow as tf

import numpy as np
from numpy.testing import assert_array_almost_equal

from gpflow import misc
from gpflow.test_util import GPflowTestCase

class TestVecToTri(GPflowTestCase):
def reference_inverse(self, matrices):
# This is the inverse operation of the vec_to_tri op being tested.
D, N, _ = matrices.shape
M = (N * (N + 1)) // 2
tril_indices = np.tril_indices(N)
output = np.zeros((D, M))
for vector_index in range(D):
matrix = matrices[vector_index, :]
output[vector_index, :] = matrix[tril_indices]
return output

def get_example_matrices(self, D, N ):
rng = np.random.RandomState(1)
random_matrices = rng.randn(D, N, N)
for matrix_index in range(D):
for row_index in range(N):
for col_index in range(N):
if col_index > row_index:
random_matrices[matrix_index, row_index, col_index] = 0.
return random_matrices

def test_basic_functionality(self):
with self.test_context() as sess:
N = 3
D = 3
reference_matrices = self.get_example_matrices(D, N)
input_vector_tensor = tf.constant(self.reference_inverse(reference_matrices))

test_matrices_tensor = misc.vec_to_tri(input_vector_tensor, N)
test_matrices = sess.run(test_matrices_tensor)
assert_array_almost_equal(reference_matrices, test_matrices)

def test_differentiable(self):
with self.test_context() as sess:
N = 3
D = 3
reference_matrices = self.get_example_matrices(D, N)
input_vector_array = self.reference_inverse(reference_matrices)
input_vector_tensor = tf.constant(input_vector_array)

test_matrices_tensor = misc.vec_to_tri(input_vector_tensor, N)
reduced_sum = tf.reduce_sum(test_matrices_tensor)