def testGramMatrix(self):
# Test Gram Matrix of a batch of TT vectors.
tt_vectors = initializers.random_matrix_batch(((2, 3), None),
batch_size=5)
res_actual = batch_ops.gram_matrix(tt_vectors)
full_vectors = tf.reshape(ops.full(tt_vectors), (5, 6))
res_desired = tf.matmul(full_vectors, tf.transpose(full_vectors))
res_desired = tf.squeeze(res_desired)
with self.test_session() as sess:
res_actual_val, res_desired_val = sess.run(
(res_actual, res_desired))
self.assertAllClose(res_desired_val, res_actual_val)
def testGramMatrixWithMatrix(self):
# Test Gram Matrix of a batch of TT vectors with providing a matrix, so we
# should compute
# res[i, j] = tt_vectors[i] ^ T * matrix * tt_vectors[j]
tt_vectors = initializers.random_matrix_batch(((2, 3), None),
batch_size=4)
matrix = initializers.random_matrix(((2, 3), (2, 3)))
res_actual = batch_ops.gram_matrix(tt_vectors, matrix)
full_vectors = tf.reshape(ops.full(tt_vectors), (4, 6))
with self.test_session() as sess:
res = sess.run((res_actual, full_vectors, ops.full(matrix)))
res_actual_val, vectors_val, matrix_val = res
res_desired_val = np.zeros((4, 4))
for i in range(4):
for j in range(4):
curr_val = np.dot(vectors_val[i], matrix_val)
curr_val = np.dot(curr_val, vectors_val[j])
res_desired_val[i, j] = curr_val
self.assertAllClose(res_desired_val,
res_actual_val,
atol=1e-5,
rtol=1e-5)