code: def test_initial_states_rank0_checkpointing(self) -> None:
      with tempfile.TemporaryDirectory() as tmpdir:
          lc = get_launch_config(
              world_size=2, rdzv_endpoint=os.path.join(tmpdir, "rdzv")
          )
          pet.elastic_launch(
              lc,
              entrypoint=self._run_trainer_initial_states_checkpointing,
          )()
  
imports: import copy
  import dataclasses
  import logging
  import os
  import tempfile
  import unittest
  from typing import Any, Dict, List, Optional
  from unittest.mock import MagicMock, patch
  import torch
  import torch.distributed
  import torch.distributed.launcher
  from torchrec.metrics.auc import AUCMetric
  from torchrec.metrics.metric_module import generate_metric_module, MetricValue, RecMetricModule, StateMetric, StateMetricEnum
  from torchrec.metrics.metrics_config import _DEFAULT_WINDOW_SIZE, DefaultMetricsConfig, DefaultTaskInfo, EmptyMetricsConfig, RecMetricDef, RecMetricEnum
  from torchrec.metrics.model_utils import parse_task_model_outputs
  from torchrec.metrics.rec_metric import RecMetricList, RecTaskInfo
  from torchrec.metrics.test_utils import gen_test_batch, get_launch_config
  from torchrec.metrics.throughput import ThroughputMetric
label_desc: Use image node_id 6 for calling the MetricModuleTest obj's underlying member method code with example usage: obj.test_initial_states_rank0_checkpointing() without return types