def test_differs_given_different_seed(self):
signs_1 = tf_utils.random_signs(100, tf.constant([123, 456], tf.int64))
signs_2 = tf_utils.random_signs(100, tf.constant([1234, 456],
tf.int64))
signs_1, signs_2 = self.evaluate([signs_1, signs_2])
self.assertFalse(np.array_equal(signs_1, signs_2))
def test_expected_dtype(self, dtype):
signs = tf_utils.random_signs(10, tf.constant([123, 456], tf.int64),
dtype)
self.assertEqual(dtype, signs.dtype)
signs = self.evaluate(signs)
self._assert_signs(signs)
def test_expected_output_values(self, num_elements):
signs = tf_utils.random_signs(num_elements,
tf.constant([123, 456], tf.int64))
signs = self.evaluate(signs)
self._assert_signs(signs)
def test_both_values_present(self):
signs = tf_utils.random_signs(1000, tf.constant([123, 456], tf.int64))
signs = self.evaluate(signs)
self._assert_signs(signs)
self.assertGreater(sum(np.isclose(1.0, signs)), 400)
self.assertGreater(sum(np.isclose(-1.0, signs)), 400)
def _random_signs(self, num_elements, seed, dtype):
return tf_utils.random_signs(num_elements, seed, dtype)
