def graph_fn(): t1 = tf.constant([1, 2, 3], dtype=tf.int32) clip_t1 = shape_utils.clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) clip_t2 = shape_utils.clip_tensor(t2, tf.constant(2)) return clip_t1, clip_t2
def test_clip_tensor_using_tensor_input(self): t1 = tf.constant([1, 2, 3], dtype=tf.int32) clip_t1 = shape_utils.clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) clip_t2 = shape_utils.clip_tensor(t2, tf.constant(2)) with self.test_session() as sess: clip_t1_result, clip_t2_result = sess.run([clip_t1, clip_t2]) self.assertAllEqual([1, 2], clip_t1_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], clip_t2_result)
def graph_fn(): t1 = tf.constant([1, 2, 3], dtype=tf.int32) clip_t1 = shape_utils.clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) clip_t2 = shape_utils.clip_tensor(t2, 2) self.assertEqual(2, clip_t1.get_shape()[0]) self.assertEqual(2, clip_t2.get_shape()[0]) return clip_t1, clip_t2
def graph_fn(): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) return tt1, tt2, tt3, tt4
def graph_fn(): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) return tt1, tt2, tt3, tt4
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)