def test_stop_pipeline_non_existent(self):
with self._mlmd_connection as m:
# Stop pipeline without creating one.
with self.assertRaises(
status_lib.StatusNotOkError) as exception_context:
pipeline_ops.stop_pipeline(
m,
task_lib.PipelineUid(pipeline_id='foo',
pipeline_run_id=None))
self.assertEqual(status_lib.Code.NOT_FOUND,
exception_context.exception.code)
# Initiate pipeline start and mark it completed.
pipeline1 = _test_pipeline('pipeline1')
execution = pipeline_ops.initiate_pipeline_start(m, pipeline1)
pipeline_uid = task_lib.PipelineUid.from_pipeline(pipeline1)
pipeline_ops._initiate_pipeline_stop(m, pipeline_uid)
execution.last_known_state = metadata_store_pb2.Execution.COMPLETE
m.store.put_executions([execution])
# Try to initiate stop again.
with self.assertRaises(
status_lib.StatusNotOkError) as exception_context:
pipeline_ops.stop_pipeline(m, pipeline_uid)
self.assertEqual(status_lib.Code.ALREADY_EXISTS,
exception_context.exception.code)
def test_initiate_pipeline_stop(self):
with self._mlmd_connection as m:
pipeline1 = _test_pipeline('pipeline1')
pipeline_ops.initiate_pipeline_start(m, pipeline1)
pipeline_uid = task_lib.PipelineUid.from_pipeline(pipeline1)
pipeline_ops._initiate_pipeline_stop(m, pipeline_uid)
# Verify MLMD state.
executions = m.store.get_executions_by_type(
pipeline_ops._ORCHESTRATOR_RESERVED_ID)
self.assertLen(executions, 1)
execution = executions[0]
self.assertEqual(
1, execution.custom_properties[
pipeline_ops._STOP_INITIATED].int_value)
def test_initiate_pipeline_stop(self):
with self._mlmd_connection as m:
pipeline1 = _test_pipeline('pipeline1')
pipeline_ops.initiate_pipeline_start(m, pipeline1)
pipeline_uid = task_lib.PipelineUid.from_pipeline(pipeline1)
pipeline_state = pipeline_ops._initiate_pipeline_stop(
m, pipeline_uid)
self.assertTrue(pipeline_state.is_stop_initiated())
def test_stop_initiated_async_pipelines(self, mock_gen_task_from_active,
mock_async_task_gen,
mock_sync_task_gen):
with self._mlmd_connection as m:
pipeline1 = _test_pipeline('pipeline1')
pipeline1.nodes.add().pipeline_node.node_info.id = 'Transform'
pipeline1.nodes.add().pipeline_node.node_info.id = 'Trainer'
pipeline1.nodes.add().pipeline_node.node_info.id = 'Evaluator'
pipeline_ops.initiate_pipeline_start(m, pipeline1)
pipeline1_execution = pipeline_ops._initiate_pipeline_stop(
m, task_lib.PipelineUid.from_pipeline(pipeline1))
task_queue = tq.TaskQueue()
# For the stop-initiated pipeline, "Transform" execution task is in queue,
# "Trainer" has an active execution in MLMD but no task in queue,
# "Evaluator" has no active execution.
task_queue.enqueue(
test_utils.create_exec_node_task(node_uid=task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id='pipeline1',
pipeline_run_id=None),
node_id='Transform')))
transform_task = task_queue.dequeue(
) # simulates task being processed
mock_gen_task_from_active.side_effect = [
test_utils.create_exec_node_task(node_uid=task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id='pipeline1',
pipeline_run_id=None),
node_id='Trainer'),
is_cancelled=True), None,
None, None, None
]
pipeline_ops.generate_tasks(m, task_queue)
# There are no active pipelines so these shouldn't be called.
mock_async_task_gen.assert_not_called()
mock_sync_task_gen.assert_not_called()
# Simulate finishing the "Transform" ExecNodeTask.
task_queue.task_done(transform_task)
# CancelNodeTask for the "Transform" ExecNodeTask should be next.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_cancel_node_task(task))
self.assertEqual('Transform', task.node_uid.node_id)
# ExecNodeTask for "Trainer" is next.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual('Trainer', task.node_uid.node_id)
self.assertTrue(task_queue.is_empty())
mock_gen_task_from_active.assert_has_calls([
mock.call(m,
pipeline1,
pipeline1.nodes[1].pipeline_node,
mock.ANY,
is_cancelled=True),
mock.call(m,
pipeline1,
pipeline1.nodes[2].pipeline_node,
mock.ANY,
is_cancelled=True)
])
self.assertEqual(2, mock_gen_task_from_active.call_count)
# Pipeline execution should continue to be active since active node
# executions were found in the last call to `generate_tasks`.
[execution
] = m.store.get_executions_by_id([pipeline1_execution.id])
self.assertTrue(execution_lib.is_execution_active(execution))
# Call `generate_tasks` again; this time there are no more active node
# executions so the pipeline should be marked as cancelled.
pipeline_ops.generate_tasks(m, task_queue)
self.assertTrue(task_queue.is_empty())
[execution
] = m.store.get_executions_by_id([pipeline1_execution.id])
self.assertEqual(metadata_store_pb2.Execution.CANCELED,
execution.last_known_state)
