def testPadTensorToBatchSize(self):
with self.session():
# Cannot pad a 0-dimensional Tensor.
tensor_0d = tf.constant(1)
with self.assertRaises(ValueError):
dataset_ops.pad_tensor_to_batch_size(tensor_0d, 10)
# 1-dimensional Tensor. Un-padded batch size is 5.
tensor_1d = tf.range(5, dtype=tf.int32)
self.assertEqual([5], tensor_1d.shape)
self.assertAllEqual([0, 1, 2, 3, 4], tensor_1d.eval())
tensor_1d_pad5 = dataset_ops.pad_tensor_to_batch_size(tensor_1d, 5)
self.assertEqual([5], tensor_1d_pad5.shape)
self.assertAllEqual([0, 1, 2, 3, 4], tensor_1d_pad5.eval())
tensor_1d_pad8 = dataset_ops.pad_tensor_to_batch_size(tensor_1d, 8)
self.assertEqual([8], tensor_1d_pad8.shape)
self.assertAllEqual([0, 1, 2, 3, 4, 0, 0, 0], tensor_1d_pad8.eval())
# 2-dimensional Tensor. Un-padded batch size is 3.
tensor_2d = tf.reshape(tf.range(9, dtype=tf.int32), [3, 3])
self.assertEqual([3, 3], tensor_2d.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8]], tensor_2d.eval())
tensor_2d_pad3 = dataset_ops.pad_tensor_to_batch_size(tensor_2d, 3)
self.assertEqual([3, 3], tensor_2d_pad3.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8]],
tensor_2d_pad3.eval())
tensor_2d_pad4 = dataset_ops.pad_tensor_to_batch_size(tensor_2d, 4)
self.assertEqual([4, 3], tensor_2d_pad4.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 0, 0]],
tensor_2d_pad4.eval())
def testPadTensorToBatchSize(self):
with self.test_session():
# Cannot pad a 0-dimensional Tensor.
tensor_0d = tf.constant(1)
with self.assertRaises(ValueError):
dataset_ops.pad_tensor_to_batch_size(tensor_0d, 10)
# 1-dimensional Tensor. Un-padded batch size is 5.
tensor_1d = tf.range(5, dtype=tf.int32)
self.assertEqual([5], tensor_1d.shape)
self.assertAllEqual([0, 1, 2, 3, 4], tensor_1d.eval())
tensor_1d_pad5 = dataset_ops.pad_tensor_to_batch_size(tensor_1d, 5)
self.assertEqual([5], tensor_1d_pad5.shape)
self.assertAllEqual([0, 1, 2, 3, 4], tensor_1d_pad5.eval())
tensor_1d_pad8 = dataset_ops.pad_tensor_to_batch_size(tensor_1d, 8)
self.assertEqual([8], tensor_1d_pad8.shape)
self.assertAllEqual([0, 1, 2, 3, 4, 0, 0, 0], tensor_1d_pad8.eval())
# 2-dimensional Tensor. Un-padded batch size is 3.
tensor_2d = tf.reshape(tf.range(9, dtype=tf.int32), [3, 3])
self.assertEqual([3, 3], tensor_2d.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8]], tensor_2d.eval())
tensor_2d_pad3 = dataset_ops.pad_tensor_to_batch_size(tensor_2d, 3)
self.assertEqual([3, 3], tensor_2d_pad3.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8]],
tensor_2d_pad3.eval())
tensor_2d_pad4 = dataset_ops.pad_tensor_to_batch_size(tensor_2d, 4)
self.assertEqual([4, 3], tensor_2d_pad4.shape)
self.assertAllEqual([[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 0, 0]],
tensor_2d_pad4.eval())