def test_transform(self):
with job_config('task_1'):
o = ops.read_dataset(read_dataset_processor=None,
dataset_info=DatasetMeta(name='dataset'))
t = ops.transform(input=o, transform_processor=None)
ops.write_dataset(input=t,
dataset_info=DatasetMeta(name='dataset'))
self.assertEqual(3, len(current_graph().nodes))
self.assertEqual(2, len(current_graph().edges))
def test_model_validate(self):
with job_config('task_1'):
o = ops.read_dataset(read_dataset_processor=None,
dataset_info=DatasetMeta(name='dataset'))
t = ops.model_validate(input=o,
model_validation_processor=None,
model_info=ModelMeta(name='model'),
name='a')
self.assertEqual(2, len(current_graph().nodes))
self.assertEqual(1, len(current_graph().edges))
n = self.get_node_by_name('a')
self.assertEqual('model', n.node_config.get('model_info').name)
def test_read_write_dataset(self):
with job_config('task_1'):
o = ops.read_dataset(read_dataset_processor=None,
dataset_info=DatasetMeta(name='source'))
ops.write_dataset(input=o, dataset_info=DatasetMeta(name='sink'))
self.assertEqual(2, len(current_graph().nodes))
self.assertEqual(1, len(current_graph().edges))
node_list = list(current_graph().nodes.values())
for node in node_list:
if isinstance(node, ReadDatasetNode):
self.assertEqual('source',
node.node_config.get('dataset').name)
elif isinstance(node, WriteDatasetNode):
self.assertEqual('sink', node.node_config.get('dataset').name)
self.assertEqual('mock', node.config.job_type)
def test_train(self):
with job_config('task_1'):
o = ops.read_dataset(read_dataset_processor=None,
dataset_info=DatasetMeta(name='dataset'))
t = ops.train(input=o,
training_processor=None,
output_num=1,
model_info=ModelMeta(name='model'),
name='a')
ops.write_dataset(input=t,
dataset_info=DatasetMeta(name='dataset'))
self.assertEqual(3, len(current_graph().nodes))
self.assertEqual(2, len(current_graph().edges))
n = self.get_node_by_name('a')
self.assertEqual('model', n.node_config.get('model_info').name)