class_docstr: Mixes eager and idle worker threads each taking tasks from a different inter-process queue and
  putting the tasks into a single (worker's internal) `task_queue`. Eager worker thread takes
  tasks from the dedicated queue, i.e. tasks that can be processed only by the given worker
  process. Idle worker thread takes tasks from the general queue, i.e. tasks that can be
  processed by any worker process from the pool.
  Eager worker reads tasks whenever any is available and moves them into the worker's internal
  queue, whereas idle worker serves as a fallback that aims to read a single item only if
  the internal queue is empty and the main thread does not process any task (is idle).
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code: def get_recv_queues(self):
      return [self.general_task_queue, self.dedicated_task_queue]
  
imports: from typing import List, Optional, Tuple
  import threading
  import traceback
  import socket
  from collections import deque
  from multiprocessing import reduction
  from nvidia.dali._utils.external_source_impl import SourceKind, _is_generator_function
  from nvidia.dali._multiproc.shared_batch import SharedBatchWriter, SharedBatchMeta, BufShmChunk, assert_valid_data_type, read_shm_message, write_shm_message
  from nvidia.dali._multiproc.messages import CompletedTask, WorkerArgs, ShmMessageDesc, ScheduledTask
  from nvidia.dali._multiproc.shared_queue import Dispatcher
label_desc: Use image node_id 2 for calling the MixedTaskReceiver obj's underlying member method code with example usage: obj.get_recv_queues() and returns: list