def testNaiveDiagonalFactorInit(self):
with tf_ops.Graph().as_default():
random_seed.set_random_seed(200)
tensor = array_ops.ones((2, 3), name='a/b/c')
factor = ff.NaiveDiagonalFactor((tensor, ), 32)
factor.instantiate_cov_variables()
self.assertEqual([6, 1], factor.get_cov().get_shape().as_list())
def testMakeCovarianceUpdateOp(self):
with tf_ops.Graph().as_default(), self.test_session() as sess:
random_seed.set_random_seed(200)
tensor = array_ops.constant([1., 2.], name='a/b/c')
factor = ff.NaiveDiagonalFactor((tensor,), 2)
sess.run(tf_variables.global_variables_initializer())
new_cov = sess.run(factor.make_covariance_update_op(.5))
self.assertAllClose([[0.75], [1.5]], new_cov)
def testNaiveDiagonalFactorInitFloat64(self):
with tf_ops.Graph().as_default():
dtype = dtypes.float64_ref
random_seed.set_random_seed(200)
tensor = array_ops.ones((2, 3), dtype=dtype, name='a/b/c')
factor = ff.NaiveDiagonalFactor((tensor,), 32)
cov = factor.get_cov()
self.assertEqual(cov.dtype, dtype)
self.assertEqual([6, 1], cov.get_shape().as_list())
