def testFullyConnectedMultiKFInit(self):
with tf.Graph().as_default():
tf.set_random_seed(200)
tensor = tf.ones((2, 3), name='a/b/c')
factor = ff.FullyConnectedMultiKF(((tensor, ), ), has_bias=False)
factor.instantiate_cov_variables()
self.assertEqual([3, 3], factor.cov.get_shape().as_list())
def testMakeCovarianceUpdateOpNoBias(self):
with tf.Graph().as_default(), self.test_session() as sess:
tf.set_random_seed(200)
tensor = tf.constant([[1., 2.], [3., 4.]], name='a/b/c')
factor = ff.FullyConnectedMultiKF(((tensor, ), ))
factor.instantiate_cov_variables()
sess.run(tf.global_variables_initializer())
new_cov = sess.run(factor.make_covariance_update_op(.5))
self.assertAllClose([[3, 3.5], [3.5, 5.5]], new_cov)
def testFullyConnectedMultiKFInitFloat64(self):
with tf.Graph().as_default():
dtype = dtypes.float64_ref
tf.set_random_seed(200)
tensor = tf.ones((2, 3), dtype=dtype, name='a/b/c')
factor = ff.FullyConnectedMultiKF(((tensor, ), ), has_bias=False)
factor.instantiate_cov_variables()
cov = factor.cov
self.assertEqual(cov.dtype, dtype)
self.assertEqual([3, 3], cov.get_shape().as_list())