def step(method_name, method, *args, **kwargs):
readonly = getattr(method, "__virtual_actor_readonly__", False)
flattened_args = self.flatten_args(method_name, args, kwargs)
actor_id = workflow_context.get_current_workflow_id()
if not readonly:
if method_name == "__init__":
state_ref = None
else:
ws = WorkflowStorage(actor_id, get_global_storage())
state_ref = WorkflowRef(ws.get_entrypoint_step_id())
# This is a hack to insert a positional argument.
flattened_args = [signature.DUMMY_TYPE, state_ref
] + flattened_args
workflow_inputs = serialization_context.make_workflow_inputs(
flattened_args)
if readonly:
_actor_method = _wrap_readonly_actor_method(
actor_id, self.cls, method_name)
step_type = StepType.READONLY_ACTOR_METHOD
else:
_actor_method = _wrap_actor_method(self.cls, method_name)
step_type = StepType.ACTOR_METHOD
# TODO(suquark): Support actor options.
workflow_data = WorkflowData(
func_body=_actor_method,
step_type=step_type,
inputs=workflow_inputs,
max_retries=1,
catch_exceptions=False,
ray_options={},
name=None,
)
wf = Workflow(workflow_data)
return wf
def _record_step_status(step_id: "StepID",
status: "WorkflowStatus",
outputs: List["ObjectRef"] = []) -> None:
workflow_id = workflow_context.get_current_workflow_id()
workflow_manager = get_management_actor()
ray.get(
workflow_manager.update_step_status.remote(workflow_id, step_id,
status, outputs))
def _record_step_status(step_id: "StepID", status: "WorkflowStatus") -> None:
workflow_id = workflow_context.get_current_workflow_id()
workflow_manager = ray.get_actor(MANAGEMENT_ACTOR_NAME)
ray.get(
workflow_manager.update_step_status.remote(workflow_id, step_id,
status))
def _workflow_step_executor(
step_type: StepType, func: Callable,
context: workflow_context.WorkflowStepContext, step_id: "StepID",
baked_inputs: "_BakedWorkflowInputs", outer_most_step_id: "StepID",
catch_exceptions: bool, max_retries: int,
last_step_of_workflow: bool) -> Any:
"""Executor function for workflow step.
Args:
step_type: The type of workflow step.
func: The workflow step function.
context: Workflow step context. Used to access correct storage etc.
step_id: The ID of the step.
baked_inputs: The processed inputs for the step.
outer_most_step_id: See "step_executor.execute_workflow" for
explanation.
catch_exceptions: If set to be true, return
(Optional[Result], Optional[Error]) instead of Result.
max_retries: Max number of retries encounter of a failure.
last_step_of_workflow: The step that generates the output of the
workflow (including nested steps).
Returns:
Workflow step output.
"""
workflow_context.update_workflow_step_context(context, step_id)
args, kwargs = _resolve_step_inputs(baked_inputs)
store = workflow_storage.get_workflow_storage()
try:
persisted_output, volatile_output = _wrap_run(
func, step_type, step_id, catch_exceptions, max_retries, *args,
**kwargs)
except Exception as e:
commit_step(store, step_id, None, e, outer_most_step_id)
raise e
if step_type == StepType.READONLY_ACTOR_METHOD:
if isinstance(volatile_output, Workflow):
raise TypeError(
"Returning a Workflow from a readonly virtual actor "
"is not allowed.")
assert not isinstance(persisted_output, Workflow)
else:
store = workflow_storage.get_workflow_storage()
commit_step(store, step_id, persisted_output, None, outer_most_step_id)
if isinstance(persisted_output, Workflow):
if step_type == StepType.FUNCTION:
# Passing down outer most step so inner nested steps would
# access the same outer most step.
if not outer_most_step_id:
# The current workflow step returns a nested workflow, and
# there is no outer step for the current step. So the
# current step is the outer most step for the inner nested
# workflow steps.
outer_most_step_id = workflow_context.get_current_step_id()
assert volatile_output is None
# execute sub-workflow
result = execute_workflow(persisted_output, outer_most_step_id,
last_step_of_workflow)
# When virtual actor returns a workflow in the method,
# the volatile_output and persisted_output will be put together
persisted_output = result.persisted_output
volatile_output = result.volatile_output
elif last_step_of_workflow:
# advance the progress of the workflow
store.advance_progress(step_id)
_record_step_status(step_id, WorkflowStatus.SUCCESSFUL)
logger.info(get_step_status_info(WorkflowStatus.SUCCESSFUL))
if isinstance(volatile_output, Workflow):
# This is the case where a step method is called in the virtual actor.
# We need to run the method to get the final result.
assert step_type == StepType.ACTOR_METHOD
volatile_output = volatile_output.run_async(
workflow_context.get_current_workflow_id())
return persisted_output, volatile_output
def _workflow_id(self):
from ray.experimental.workflow.workflow_context import \
get_current_workflow_id
return get_current_workflow_id()