code: def _workflow_task_executor_remote(
      func: Callable,
      context: "WorkflowTaskContext",
      job_id: str,
      task_id: "TaskID",
      baked_inputs: "_BakedWorkflowInputs",
      runtime_options: "WorkflowTaskRuntimeOptions",
  ) -> Any:
      """The remote version of '_workflow_task_executor'."""
      with workflow_context.workflow_logging_context(job_id):
          return _workflow_task_executor(
              func, context, task_id, baked_inputs, runtime_options
          )
  
file_path: ray/python/ray/workflow/task_executor.py
imports: import time
  from dataclasses import dataclass
  import logging
  from typing import List, Tuple, Any, Dict, Callable, TYPE_CHECKING
  import ray
  from ray import ObjectRef
  from ray._private import signature
  from ray.dag import DAGNode
  from ray.workflow import workflow_context
  from ray.workflow.workflow_context import get_task_status_info
  from ray.workflow import serialization_context
  from ray.workflow import workflow_storage
  from ray.workflow.common import WorkflowStatus, WorkflowExecutionMetadata, TaskType, TaskID, WorkflowRef, CheckpointMode
  from ray.workflow.workflow_state import WorkflowExecutionState
  from ray.workflow.workflow_state_from_dag import workflow_state_from_dag
label_desc: Use image node_id 3 for calling a global function with example usage: _workflow_task_executor_remote(func, context, job_id, task_id, baked_inputs, runtime_options) and returns: _workflow_task_executor