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)