code: def test_prefix_metric_keys():
      """Test that metric key names are converted correctly."""
      metrics = {"1": 1.0, "2": 2.0, "3": 3.0}
      prefix = "foo"
      separator = "."
      converted_metrics = _prefix_metric_keys(
          metrics, prefix, separator
      )
      assert converted_metrics == {
          "foo.1": 1.0,
          "foo.2": 2.0,
          "foo.3": 3.0,
      }
  
imports: import csv
  import os
  import re
  from typing import Dict, Optional
  from unittest import mock
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.accelerators.cpu import _CPU_PERCENT, _CPU_SWAP_PERCENT, _CPU_VM_PERCENT, get_cpu_stats
  from lightning.pytorch.callbacks import DeviceStatsMonitor
  from lightning.pytorch.callbacks.device_stats_monitor import _prefix_metric_keys
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loggers import CSVLogger
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.rank_zero import rank_zero_only
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 5 for calling a global function with example usage: test_prefix_metric_keys() without return types