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)