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)