def testFullFactorInit(self):
with tf.Graph().as_default():
tf.set_random_seed(200)
tensor = tf.ones((2, 3), name='a/b/c')
factor = ff.FullFactor((tensor, ), 32)
factor.instantiate_cov_variables()
self.assertEqual([6, 6], factor.cov.get_shape().as_list())
def testMakeCovarianceUpdateOp(self):
with tf.Graph().as_default(), self.test_session() as sess:
tf.set_random_seed(200)
tensor = tf.constant([1., 2.], name='a/b/c')
factor = ff.FullFactor((tensor, ), 2)
factor.instantiate_cov_variables()
sess.run(tf.global_variables_initializer())
new_cov = sess.run(factor.make_covariance_update_op(.5))
self.assertAllClose([[0.75, 0.5], [0.5, 1.5]], new_cov)
def testFullFactorInitFloat64(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.FullFactor((tensor, ), 32)
factor.instantiate_cov_variables()
cov = factor.cov
self.assertEqual(cov.dtype, dtype)
self.assertEqual([6, 6], cov.get_shape().as_list())