code: def is_available(cls) -> bool:
      # todo: check if neuron-ls is available and if yes, what it reports. see:
      # https://awsdocs-neuron.readthedocs-hosted.com/en/latest/tools/neuron-sys-tools/neuron-ls.html
      if not pathlib.Path(NEURON_LS_COMMAND[0]).exists():
          return False
      # need to be extra careful as neuron tools could be pre-installed
      # on some systems that do not have the hardware
      try:
          # redirect stderr to null to avoid printing errors to the console
          # todo: alternative: check /dev/neuron0 ? sysfs support coming soon in neuron tools
          output = subprocess.check_output(
              NEURON_LS_COMMAND,
              universal_newlines=True,
              stderr=subprocess.DEVNULL,
          ).strip()
          if len(json.loads(output)) > 0:
              return True
      except (
          OSError,
          ValueError,
          TypeError,
          subprocess.CalledProcessError,
      ):
          pass
  
      return False
  
imports: import collections
  import dataclasses
  import json
  import logging
  import os
  import pathlib
  import shutil
  import subprocess
  import sys
  import tempfile
  import threading
  import time
  from collections import deque
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
  from wandb.sdk.lib import telemetry
  from .aggregators import aggregate_mean
  from .asset_registry import asset_registry
  from .interfaces import Interface, Metric, MetricsMonitor
label_desc: Use image node_id 2 for calling the Trainium obj's underlying member method code with example usage: obj.is_available(cls) and returns: False, False, True