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)