def test_taxi_pipeline_construction_and_definition_file_exists(self):
# Import creates the pipeline.
from tfx.examples.chicago_taxi_pipeline import taxi_pipeline_kubeflow # pylint: disable=g-import-not-at-top
logical_pipeline = taxi_pipeline_kubeflow._create_pipeline()
self.assertEqual(9, len(logical_pipeline.components))
file_path = os.path.join(self.test_dir,
'chicago_taxi_pipeline_kubeflow.tar.gz')
self.assertTrue(tf.gfile.Exists(file_path))
def testTaxiPipelineConstructionAndDefinitionFileExists(self):
logical_pipeline = taxi_pipeline_kubeflow._create_pipeline(
pipeline_name=taxi_pipeline_kubeflow._pipeline_name,
pipeline_root=taxi_pipeline_kubeflow._pipeline_root,
query=taxi_pipeline_kubeflow._query,
module_file=taxi_pipeline_kubeflow._module_file,
beam_pipeline_args=taxi_pipeline_kubeflow._beam_pipeline_args,
ai_platform_training_args=taxi_pipeline_kubeflow.
_ai_platform_training_args,
ai_platform_serving_args=taxi_pipeline_kubeflow.
_ai_platform_serving_args)
self.assertEqual(9, len(logical_pipeline.components))
KubeflowDagRunner().run(logical_pipeline)
file_path = os.path.join(self._tmp_dir,
'chicago_taxi_pipeline_kubeflow.tar.gz')
self.assertTrue(tf.io.gfile.exists(file_path))