def _exec_node_tasks():
for pipeline_id in ('pipeline1', 'pipeline2'):
yield [
test_utils.create_exec_node_task(
node_uid=task_lib.
NodeUid(pipeline_uid=task_lib.PipelineUid(
pipeline_id=pipeline_id, pipeline_run_id=None),
node_id='Transform')),
test_utils.create_exec_node_task(
node_uid=task_lib.
NodeUid(pipeline_uid=task_lib.PipelineUid(
pipeline_id=pipeline_id, pipeline_run_id=None),
node_id='Trainer'))
]
def test_task_ids(self):
pipeline_uid = task_lib.PipelineUid(pipeline_id='pipeline')
node_uid = task_lib.NodeUid(pipeline_uid=pipeline_uid, node_id='Trainer')
exec_node_task = test_utils.create_exec_node_task(node_uid)
self.assertEqual(('ExecNodeTask', node_uid), exec_node_task.task_id)
cancel_node_task = task_lib.CancelNodeTask(node_uid=node_uid)
self.assertEqual(('CancelNodeTask', node_uid), cancel_node_task.task_id)
def test_scheduler_not_found(self):
task = test_utils.create_exec_node_task(node_uid=task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id='pipeline'),
node_id='Transform'),
pipeline=self._pipeline)
with self.assertRaisesRegex(ValueError, 'No task scheduler found'):
ts.TaskSchedulerRegistry.create_task_scheduler(
mock.Mock(), self._pipeline, task)
def _test_exec_node_task(node_id,
pipeline_id,
pipeline_run_id=None,
pipeline=None):
node_uid = task_lib.NodeUid(pipeline_uid=task_lib.PipelineUid(
pipeline_id=pipeline_id, pipeline_run_id=pipeline_run_id),
node_id=node_id)
return test_utils.create_exec_node_task(node_uid, pipeline=pipeline)
def test_task_type_ids(self):
self.assertEqual('ExecNodeTask', task_lib.ExecNodeTask.task_type_id())
self.assertEqual('CancelNodeTask',
task_lib.CancelNodeTask.task_type_id())
node_uid = task_lib.NodeUid(pipeline_id='pipeline',
pipeline_run_id='run0',
node_id='Trainer')
exec_node_task = test_utils.create_exec_node_task(node_uid)
self.assertEqual('ExecNodeTask', exec_node_task.task_type_id())
cancel_node_task = task_lib.CancelNodeTask(node_uid=node_uid)
self.assertEqual('CancelNodeTask', cancel_node_task.task_type_id())
def test_register_using_executor_spec_type_url(self):
# Register a fake task scheduler.
ts.TaskSchedulerRegistry.register(self._spec_type_url, _FakeTaskScheduler)
# Create a task and verify that the correct scheduler is instantiated.
task = test_utils.create_exec_node_task(
node_uid=task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id='pipeline'),
node_id='Trainer'),
pipeline=self._pipeline)
task_scheduler = ts.TaskSchedulerRegistry.create_task_scheduler(
mock.Mock(), self._pipeline, task)
self.assertIsInstance(task_scheduler, _FakeTaskScheduler)
def test_register_using_node_type_name(self):
# Register a fake task scheduler.
ts.TaskSchedulerRegistry.register(constants.IMPORTER_NODE_TYPE,
_FakeTaskScheduler)
# Create a task and verify that the correct scheduler is instantiated.
task = test_utils.create_exec_node_task(node_uid=task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id='pipeline'),
node_id='Importer'),
pipeline=self._pipeline)
task_scheduler = ts.TaskSchedulerRegistry.create_task_scheduler(
mock.Mock(), self._pipeline, task)
self.assertIsInstance(task_scheduler, _FakeTaskScheduler)
def test_registration_and_creation(self):
# Create a pipeline IR containing deployment config for testing.
deployment_config = pipeline_pb2.IntermediateDeploymentConfig()
executor_spec = pipeline_pb2.ExecutorSpec.PythonClassExecutorSpec(
class_path='trainer.TrainerExecutor')
deployment_config.executor_specs['Trainer'].Pack(executor_spec)
pipeline = pipeline_pb2.Pipeline()
pipeline.deployment_config.Pack(deployment_config)
# Register a fake task scheduler.
spec_type_url = deployment_config.executor_specs['Trainer'].type_url
ts.TaskSchedulerRegistry.register(spec_type_url, _FakeTaskScheduler)
# Create a task and verify that the correct scheduler is instantiated.
task = test_utils.create_exec_node_task(node_uid=task_lib.NodeUid(
pipeline_id='pipeline', pipeline_run_id=None, node_id='Trainer'))
task_scheduler = ts.TaskSchedulerRegistry.create_task_scheduler(
mock.Mock(), pipeline, task)
self.assertIsInstance(task_scheduler, _FakeTaskScheduler)
def test_handling_finalize_node_task(self, task_gen):
with self._mlmd_connection as m:
pipeline = _test_pipeline('pipeline1')
pipeline.nodes.add().pipeline_node.node_info.id = 'Transform'
pipeline.nodes.add().pipeline_node.node_info.id = 'Trainer'
pipeline_ops.initiate_pipeline_start(m, pipeline)
pipeline_uid = task_lib.PipelineUid.from_pipeline(pipeline)
finalize_reason = status_lib.Status(code=status_lib.Code.ABORTED,
message='foo bar')
task_gen.return_value.generate.side_effect = [
[
test_utils.create_exec_node_task(
task_lib.NodeUid(pipeline_uid=pipeline_uid,
node_id='Transform')),
task_lib.FinalizeNodeTask(node_uid=task_lib.NodeUid(
pipeline_uid=pipeline_uid, node_id='Trainer'),
status=finalize_reason)
],
]
task_queue = tq.TaskQueue()
pipeline_ops.orchestrate(m, task_queue,
service_jobs.DummyServiceJobManager())
task_gen.return_value.generate.assert_called_once()
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual(
test_utils.create_node_uid('pipeline1', 'Transform'),
task.node_uid)
# Load pipeline state and verify node stop initiation.
with pstate.PipelineState.load(m, pipeline_uid) as pipeline_state:
self.assertEqual(
finalize_reason,
pipeline_state.node_stop_initiated_reason(
task_lib.NodeUid(pipeline_uid=pipeline_uid,
node_id='Trainer')))
def test_active_pipelines_with_stop_initiated_nodes(self,
mock_gen_task_from_active,
mock_async_task_gen):
with self._mlmd_connection as m:
pipeline = _test_pipeline('pipeline')
pipeline.nodes.add().pipeline_node.node_info.id = 'ExampleGen'
pipeline.nodes.add().pipeline_node.node_info.id = 'Transform'
pipeline.nodes.add().pipeline_node.node_info.id = 'Trainer'
pipeline.nodes.add().pipeline_node.node_info.id = 'Evaluator'
mock_service_job_manager = mock.create_autospec(
service_jobs.ServiceJobManager, instance=True)
mock_service_job_manager.is_pure_service_node.side_effect = (
lambda _, node_id: node_id == 'ExampleGen')
example_gen_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[0].pipeline_node)
transform_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[1].pipeline_node)
transform_task = test_utils.create_exec_node_task(
node_uid=transform_node_uid)
trainer_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[2].pipeline_node)
trainer_task = test_utils.create_exec_node_task(node_uid=trainer_node_uid)
evaluator_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[3].pipeline_node)
evaluator_task = test_utils.create_exec_node_task(
node_uid=evaluator_node_uid)
cancelled_evaluator_task = test_utils.create_exec_node_task(
node_uid=evaluator_node_uid, is_cancelled=True)
pipeline_ops.initiate_pipeline_start(m, pipeline)
with pstate.PipelineState.load(
m, task_lib.PipelineUid.from_pipeline(pipeline)) as pipeline_state:
# Stop example-gen, trainer and evaluator.
pipeline_state.initiate_node_stop(
example_gen_node_uid,
status_lib.Status(code=status_lib.Code.CANCELLED))
pipeline_state.initiate_node_stop(
trainer_node_uid, status_lib.Status(code=status_lib.Code.CANCELLED))
pipeline_state.initiate_node_stop(
evaluator_node_uid, status_lib.Status(code=status_lib.Code.ABORTED))
task_queue = tq.TaskQueue()
# Simulate a new transform execution being triggered.
mock_async_task_gen.return_value.generate.return_value = [transform_task]
# Simulate ExecNodeTask for trainer already present in the task queue.
task_queue.enqueue(trainer_task)
# Simulate Evaluator having an active execution in MLMD.
mock_gen_task_from_active.side_effect = [evaluator_task]
pipeline_ops.orchestrate(m, task_queue, mock_service_job_manager)
self.assertEqual(1, mock_async_task_gen.return_value.generate.call_count)
# stop_node_services should be called on example-gen which is a pure
# service node.
mock_service_job_manager.stop_node_services.assert_called_once_with(
mock.ANY, 'ExampleGen')
# Verify that tasks are enqueued in the expected order:
# Pre-existing trainer task.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertEqual(trainer_task, task)
# CancelNodeTask for trainer.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_cancel_node_task(task))
self.assertEqual(trainer_node_uid, task.node_uid)
# ExecNodeTask with is_cancelled=True for evaluator.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(cancelled_evaluator_task, task)
# ExecNodeTask for newly triggered transform node.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertEqual(transform_task, task)
# No more tasks.
self.assertTrue(task_queue.is_empty())
def test_stop_initiated_pipelines(self, pipeline, mock_gen_task_from_active,
mock_async_task_gen, mock_sync_task_gen):
with self._mlmd_connection as m:
pipeline.nodes.add().pipeline_node.node_info.id = 'ExampleGen'
pipeline.nodes.add().pipeline_node.node_info.id = 'Transform'
pipeline.nodes.add().pipeline_node.node_info.id = 'Trainer'
pipeline.nodes.add().pipeline_node.node_info.id = 'Evaluator'
mock_service_job_manager = mock.create_autospec(
service_jobs.ServiceJobManager, instance=True)
mock_service_job_manager.is_pure_service_node.side_effect = (
lambda _, node_id: node_id == 'ExampleGen')
mock_service_job_manager.is_mixed_service_node.side_effect = (
lambda _, node_id: node_id == 'Transform')
pipeline_ops.initiate_pipeline_start(m, pipeline)
with pstate.PipelineState.load(
m, task_lib.PipelineUid.from_pipeline(pipeline)) as pipeline_state:
pipeline_state.initiate_stop(
status_lib.Status(code=status_lib.Code.CANCELLED))
pipeline_execution = pipeline_state.execution
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(
task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid.from_pipeline(pipeline),
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.from_pipeline(pipeline),
node_id='Trainer'),
is_cancelled=True), None, None, None, None
]
pipeline_ops.orchestrate(m, task_queue, mock_service_job_manager)
# 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()
# stop_node_services should be called for ExampleGen which is a pure
# service node.
mock_service_job_manager.stop_node_services.assert_called_once_with(
mock.ANY, 'ExampleGen')
mock_service_job_manager.reset_mock()
task_queue.task_done(transform_task) # Pop out 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 (with is_cancelled=True) 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.is_cancelled)
self.assertTrue(task_queue.is_empty())
mock_gen_task_from_active.assert_has_calls([
mock.call(
m,
pipeline_state.pipeline,
pipeline.nodes[2].pipeline_node,
mock.ANY,
is_cancelled=True),
mock.call(
m,
pipeline_state.pipeline,
pipeline.nodes[3].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 `orchestrate`.
[execution] = m.store.get_executions_by_id([pipeline_execution.id])
self.assertTrue(execution_lib.is_execution_active(execution))
# Call `orchestrate` again; this time there are no more active node
# executions so the pipeline should be marked as cancelled.
pipeline_ops.orchestrate(m, task_queue, mock_service_job_manager)
self.assertTrue(task_queue.is_empty())
[execution] = m.store.get_executions_by_id([pipeline_execution.id])
self.assertEqual(metadata_store_pb2.Execution.CANCELED,
execution.last_known_state)
# stop_node_services should be called on both ExampleGen and Transform
# which are service nodes.
mock_service_job_manager.stop_node_services.assert_has_calls(
[mock.call(mock.ANY, 'ExampleGen'),
mock.call(mock.ANY, 'Transform')],
any_order=True)
def test_orchestrate_active_pipelines(self, mock_async_task_gen,
mock_sync_task_gen):
with self._mlmd_connection as m:
# Sync and async active pipelines.
async_pipelines = [
_test_pipeline('pipeline1'),
_test_pipeline('pipeline2'),
]
sync_pipelines = [
_test_pipeline('pipeline3', pipeline_pb2.Pipeline.SYNC),
_test_pipeline('pipeline4', pipeline_pb2.Pipeline.SYNC),
]
for pipeline in async_pipelines + sync_pipelines:
pipeline_ops.initiate_pipeline_start(m, pipeline)
# Active executions for active async pipelines.
mock_async_task_gen.return_value.generate.side_effect = [
[
test_utils.create_exec_node_task(
task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid.from_pipeline(
async_pipelines[0]),
node_id='Transform'))
],
[
test_utils.create_exec_node_task(
task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid.from_pipeline(
async_pipelines[1]),
node_id='Trainer'))
],
]
# Active executions for active sync pipelines.
mock_sync_task_gen.return_value.generate.side_effect = [
[
test_utils.create_exec_node_task(
task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid.from_pipeline(
sync_pipelines[0]),
node_id='Trainer'))
],
[
test_utils.create_exec_node_task(
task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid.from_pipeline(
sync_pipelines[1]),
node_id='Validator'))
],
]
task_queue = tq.TaskQueue()
pipeline_ops.orchestrate(m, task_queue,
service_jobs.DummyServiceJobManager())
self.assertEqual(2, mock_async_task_gen.return_value.generate.call_count)
self.assertEqual(2, mock_sync_task_gen.return_value.generate.call_count)
# Verify that tasks are enqueued in the expected order.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual(
test_utils.create_node_uid('pipeline1', 'Transform'), task.node_uid)
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual(
test_utils.create_node_uid('pipeline2', 'Trainer'), task.node_uid)
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual(
test_utils.create_node_uid('pipeline3', 'Trainer'), task.node_uid)
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_exec_node_task(task))
self.assertEqual(
test_utils.create_node_uid('pipeline4', 'Validator'), task.node_uid)
self.assertTrue(task_queue.is_empty())
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)
def test_active_pipelines_with_stop_initiated_nodes(
self, mock_gen_task_from_active, mock_async_task_gen):
with self._mlmd_connection as m:
pipeline = _test_pipeline('pipeline')
pipeline.nodes.add().pipeline_node.node_info.id = 'Transform'
pipeline.nodes.add().pipeline_node.node_info.id = 'Trainer'
pipeline.nodes.add().pipeline_node.node_info.id = 'Evaluator'
transform_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[0].pipeline_node)
transform_task = test_utils.create_exec_node_task(
node_uid=transform_node_uid)
trainer_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[1].pipeline_node)
trainer_task = test_utils.create_exec_node_task(
node_uid=trainer_node_uid)
evaluator_node_uid = task_lib.NodeUid.from_pipeline_node(
pipeline, pipeline.nodes[2].pipeline_node)
evaluator_task = test_utils.create_exec_node_task(
node_uid=evaluator_node_uid)
cancelled_evaluator_task = test_utils.create_exec_node_task(
node_uid=evaluator_node_uid, is_cancelled=True)
pipeline_ops.initiate_pipeline_start(m, pipeline)
with pstate.PipelineState.load(
m, task_lib.PipelineUid.from_pipeline(
pipeline)) as pipeline_state:
# Stop trainer and evaluator.
pipeline_state.initiate_node_stop(trainer_node_uid)
pipeline_state.initiate_node_stop(evaluator_node_uid)
task_queue = tq.TaskQueue()
# Simulate a new transform execution being triggered.
mock_async_task_gen.return_value.generate.return_value = [
transform_task
]
# Simulate ExecNodeTask for trainer already present in the task queue.
task_queue.enqueue(trainer_task)
# Simulate Evaluator having an active execution in MLMD.
mock_gen_task_from_active.side_effect = [evaluator_task]
pipeline_ops.orchestrate(m, task_queue)
self.assertEqual(
1, mock_async_task_gen.return_value.generate.call_count)
# Verify that tasks are enqueued in the expected order:
# Pre-existing trainer task.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertEqual(trainer_task, task)
# CancelNodeTask for trainer.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(task_lib.is_cancel_node_task(task))
self.assertEqual(trainer_node_uid, task.node_uid)
# ExecNodeTask with is_cancelled=True for evaluator.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertTrue(cancelled_evaluator_task, task)
# ExecNodeTask for newly triggered transform node.
task = task_queue.dequeue()
task_queue.task_done(task)
self.assertEqual(transform_task, task)
# No more tasks.
self.assertTrue(task_queue.is_empty())
def _test_task(node_id, pipeline_id, key=''):
node_uid = task_lib.NodeUid(
pipeline_uid=task_lib.PipelineUid(pipeline_id=pipeline_id, key=key),
node_id=node_id)
return test_utils.create_exec_node_task(node_uid)
