def _resume_workflow_step_executor(
job_id: str,
workflow_id: str,
step_id: "StepID",
current_output: [ray.ObjectRef],
) -> Tuple[ray.ObjectRef, ray.ObjectRef]:
with workflow_context.workflow_logging_context(job_id):
# TODO (yic): We need better dependency management for virtual actor
# The current output will always be empty for normal workflow
# For virtual actor, if it's not empty, it means the previous job is
# running. This is a really bad one.
for ref in current_output:
try:
while isinstance(ref, ray.ObjectRef):
ref = ray.get(ref)
except Exception:
pass
try:
r = _construct_resume_workflow_from_step(workflow_id, step_id)
except Exception as e:
raise WorkflowNotResumableError(workflow_id) from e
if not isinstance(r, Workflow):
return r, None
with workflow_context.workflow_step_context(
workflow_id, last_step_of_workflow=True):
from ray.workflow.step_executor import execute_workflow
result = execute_workflow(job_id, r)
return result.persisted_output, result.volatile_output
def resume_workflow_step(
job_id: str,
workflow_id: str,
task_id: Optional[TaskID] = None,
) -> WorkflowExecutionState:
"""Resume a step of a workflow.
Args:
job_id: The ID of the job that submits the workflow execution. The ID
is used to identify the submitter of the workflow.
workflow_id: The ID of the workflow job. The ID is used to identify
the workflow.
task_id: The step to resume in the workflow.
Raises:
WorkflowNotResumableException: fail to resume the workflow.
Returns:
The execution result of the workflow, represented by Ray ObjectRef.
"""
with workflow_context.workflow_logging_context(job_id):
try:
return workflow_state_from_storage.workflow_state_from_storage(
workflow_id, task_id
)
except Exception as e:
raise WorkflowNotResumableError(workflow_id) from e
def _workflow_step_executor_remote(
func: Callable,
context: "WorkflowStepContext",
job_id: str,
task_id: "TaskID",
baked_inputs: "_BakedWorkflowInputs",
runtime_options: "WorkflowStepRuntimeOptions",
) -> Any:
"""The remote version of '_workflow_step_executor'."""
with workflow_context.workflow_logging_context(job_id):
return _workflow_step_executor(func, context, task_id, baked_inputs,
runtime_options)
