code: def task_context(self):
          
          if not hasattr(self._task_context, "initialized"):
              # Initialize task_context for the current thread.
              if ray.utils.is_main_thread():
                  # If this is running on the main thread, initialize it to
                  # NIL. The actual value will set when the worker receives
                  # a task from raylet backend.
                  self._task_context.current_task_id = TaskID.nil()
              else:
                  # If this is running on a separate thread, then the mapping
                  # to the current task ID may not be correct. Generate a
                  # random task ID so that the backend can differentiate
                  # between different threads.
                  self._task_context.current_task_id = TaskID(_random_string())
                  if getattr(self, "_multithreading_warned", False) is not True:
                      logger.warning(
                          "Calling ray.get or ray.wait in a separate thread "
                          "may lead to deadlock if the main thread blocks on "
                          "this thread and there are not enough resources to "
                          "execute more tasks")
                      self._multithreading_warned = True
  
              self._task_context.task_index = 0
              self._task_context.put_index = 1
              self._task_context.initialized = True
          return self._task_context
docs: A thread-local that contains the following attributes.
  
          current_task_id: For the main thread, this field is the ID of this
              worker's current running task; for other threads, this field is a
              fake random ID.
          task_index: The number of tasks that have been submitted from the
              current task.
          put_index: The number of objects that have been put from the current
              task.