def testBasic(self):
selector_dataset = dataset_ops.Dataset.range(10).repeat(100)
input_datasets = [
dataset_ops.Dataset.from_tensors(i).repeat(100) for i in range(10)
]
dataset = interleave_ops._DirectedInterleaveDataset(
selector_dataset, input_datasets)
next_element = self.getNext(dataset)
for _ in range(100):
for i in range(10):
self.assertEqual(i, self.evaluate(next_element()))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
def testBasic(self):
selector_dataset = dataset_ops.Dataset.range(10).repeat(100)
input_datasets = [
dataset_ops.Dataset.from_tensors(i).repeat(100) for i in range(10)
]
dataset = interleave_ops._DirectedInterleaveDataset(selector_dataset,
input_datasets)
next_element = self.getNext(dataset)
for _ in range(100):
for i in range(10):
self.assertEqual(i, self.evaluate(next_element()))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
def testBasic(self):
selector_dataset = dataset_ops.Dataset.range(10).repeat(100)
input_datasets = [
dataset_ops.Dataset.from_tensors(i).repeat(100) for i in range(10)
]
dataset = interleave_ops._DirectedInterleaveDataset(selector_dataset,
input_datasets)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for _ in range(100):
for i in range(10):
self.assertEqual(i, self.evaluate(next_element))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
def testBasic(self):
selector_dataset = dataset_ops.Dataset.range(10).repeat(100)
input_datasets = [
dataset_ops.Dataset.from_tensors(i).repeat(100) for i in range(10)
]
dataset = interleave_ops._DirectedInterleaveDataset(
selector_dataset, input_datasets)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for _ in range(100):
for i in range(10):
self.assertEqual(i, self.evaluate(next_element))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
