def testUnbatchSingleElementTupleDataset(self):
data = tuple([(math_ops.range(10), ) for _ in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
expected_types = ((dtypes.int32, ), ) * 3
data = data.batch(2)
self.assertEqual(expected_types, data.output_types)
data = data.apply(dataset_ops.unbatch())
self.assertEqual(expected_types, data.output_types)
iterator = data.make_one_shot_iterator()
op = iterator.get_next()
with self.test_session() as sess:
for i in range(10):
self.assertEqual(((i, ), ) * 3, sess.run(op))
with self.assertRaises(errors.OutOfRangeError):
sess.run(op)
def testUnbatchSingleElementTupleDataset(self):
data = tuple([(math_ops.range(10),) for _ in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
expected_types = ((dtypes.int32,),) * 3
data = data.batch(2)
self.assertEqual(expected_types, data.output_types)
data = data.apply(dataset_ops.unbatch())
self.assertEqual(expected_types, data.output_types)
iterator = data.make_one_shot_iterator()
op = iterator.get_next()
with self.test_session() as sess:
for i in range(10):
self.assertEqual(((i,),) * 3, sess.run(op))
with self.assertRaises(errors.OutOfRangeError):
sess.run(op)
def testUnbatchMultiElementTupleDataset(self):
data = tuple([(math_ops.range(10 * i,
10 * i + 10), array_ops.fill([10], "hi"))
for i in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
expected_types = ((dtypes.int32, dtypes.string), ) * 3
data = data.batch(2)
self.assertAllEqual(expected_types, data.output_types)
data = data.apply(dataset_ops.unbatch())
self.assertAllEqual(expected_types, data.output_types)
iterator = data.make_one_shot_iterator()
op = iterator.get_next()
with self.test_session() as sess:
for i in range(10):
self.assertEqual(
((i, b"hi"), (10 + i, b"hi"), (20 + i, b"hi")),
sess.run(op))
with self.assertRaises(errors.OutOfRangeError):
sess.run(op)
def testUnbatchMultiElementTupleDataset(self):
data = tuple([(math_ops.range(10 * i, 10 * i + 10),
array_ops.fill([10], "hi"))
for i in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
expected_types = ((dtypes.int32, dtypes.string),) * 3
data = data.batch(2)
self.assertAllEqual(expected_types, data.output_types)
data = data.apply(dataset_ops.unbatch())
self.assertAllEqual(expected_types, data.output_types)
iterator = data.make_one_shot_iterator()
op = iterator.get_next()
with self.test_session() as sess:
for i in range(10):
self.assertEqual(((i, b"hi"),
(10 + i, b"hi"),
(20 + i, b"hi")),
sess.run(op))
with self.assertRaises(errors.OutOfRangeError):
sess.run(op)