def testIrisPipelineNativeKeras(self):
BeamDagRunner().run(
iris_pipeline_native_keras._create_pipeline(
pipeline_name=self._pipeline_name,
data_root=self._data_root,
module_file=self._module_file,
serving_model_dir=self._serving_model_dir,
pipeline_root=self._pipeline_root,
metadata_path=self._metadata_path,
direct_num_workers=1))
self.assertTrue(tf.io.gfile.exists(self._serving_model_dir))
self.assertTrue(tf.io.gfile.exists(self._metadata_path))
expected_execution_count = 9 # 8 components + 1 resolver
metadata_config = metadata.sqlite_metadata_connection_config(
self._metadata_path)
with metadata.Metadata(metadata_config) as m:
artifact_count = len(m.store.get_artifacts())
execution_count = len(m.store.get_executions())
self.assertGreaterEqual(artifact_count, execution_count)
self.assertEqual(expected_execution_count, execution_count)
self.assertPipelineExecution()
# Runs pipeline the second time.
BeamDagRunner().run(
iris_pipeline_native_keras._create_pipeline(
pipeline_name=self._pipeline_name,
data_root=self._data_root,
module_file=self._module_file,
serving_model_dir=self._serving_model_dir,
pipeline_root=self._pipeline_root,
metadata_path=self._metadata_path,
direct_num_workers=1))
# All executions but Evaluator and Pusher are cached.
with metadata.Metadata(metadata_config) as m:
# Artifact count is increased by 3 caused by Evaluator and Pusher.
self.assertEqual(artifact_count + 3, len(m.store.get_artifacts()))
artifact_count = len(m.store.get_artifacts())
self.assertEqual(expected_execution_count * 2,
len(m.store.get_executions()))
# Runs pipeline the third time.
BeamDagRunner().run(
iris_pipeline_native_keras._create_pipeline(
pipeline_name=self._pipeline_name,
data_root=self._data_root,
module_file=self._module_file,
serving_model_dir=self._serving_model_dir,
pipeline_root=self._pipeline_root,
metadata_path=self._metadata_path,
direct_num_workers=1))
# Asserts cache execution.
with metadata.Metadata(metadata_config) as m:
# Artifact count is unchanged.
self.assertEqual(artifact_count, len(m.store.get_artifacts()))
self.assertEqual(expected_execution_count * 3,
len(m.store.get_executions()))
def testIrisPipelineNativeKeras(self):
BeamDagRunner().run(
iris_pipeline_native_keras._create_pipeline(
pipeline_name=self._pipeline_name,
data_root=self._data_root,
module_file=self._module_file,
pipeline_root=self._pipeline_root,
metadata_path=self._metadata_path))
self.assertTrue(tf.io.gfile.exists(self._metadata_path))
metadata_config = metadata.sqlite_metadata_connection_config(
self._metadata_path)
with metadata.Metadata(metadata_config) as m:
artifact_count = len(m.store.get_artifacts())
execution_count = len(m.store.get_executions())
self.assertGreaterEqual(artifact_count, execution_count)
self.assertEqual(7, execution_count)
self.assertPipelineExecution()
def testIrisPipelineNativeKerasWithTuner(self):
BeamDagRunner().run(
iris_pipeline_native_keras._create_pipeline(
pipeline_name=self._pipeline_name,
data_root=self._data_root,
module_file=self._module_file,
serving_model_dir=self._serving_model_dir,
pipeline_root=self._pipeline_root,
metadata_path=self._metadata_path,
enable_tuning=True,
direct_num_workers=1))
self.assertTrue(tf.io.gfile.exists(self._serving_model_dir))
self.assertTrue(tf.io.gfile.exists(self._metadata_path))
expected_execution_count = 10 # 9 components + 1 resolver
metadata_config = metadata.sqlite_metadata_connection_config(
self._metadata_path)
with metadata.Metadata(metadata_config) as m:
artifact_count = len(m.store.get_artifacts())
execution_count = len(m.store.get_executions())
self.assertGreaterEqual(artifact_count, execution_count)
self.assertEqual(expected_execution_count, execution_count)
self.assertPipelineExecution(True)