code: def log_metrics(self, metrics, step=None) -> None:
      fields = ["avg. free memory (MB)", "avg. peak memory (MB)"]
      for f in fields:
          assert any(f in h for h in metrics)
  
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 1 for calling the AssertTpuMetricsLogger obj's underlying member method code with example usage: obj.log_metrics(metrics, step) without return types