code: def check_gpu_support():
      try:
          data = np.random.rand(50, 2)
          label = np.random.randint(2, size=50)
          train_data = lightgbm.Dataset(data, label=label)
          params = {"num_iterations": 1, "device": "gpu"}
          lightgbm.train(params, train_set=train_data)
          device, nr_devices = get_devices()
          if nr_devices > 0 and str(device) != "cpu":
              return True
          else:
              return False
      except Exception:
          return False
  
imports: import time
  import inspect
  from typing import Dict, List, Set, Optional
  import torch
  import optuna
  import lightgbm
  import numpy
  import pandas
  from sklearn.preprocessing import OrdinalEncoder
  import optuna.integration.lightgbm
  from type_infer.dtype import dtype
  from lightwood.encoder.base import BaseEncoder
  from lightwood.helpers.log import log
  from lightwood.mixer.base import BaseMixer
  from lightwood.helpers.device import get_devices
  from lightwood.api.types import PredictionArguments
  from lightwood.data.encoded_ds import EncodedDs
label_desc: Use image node_id 1 for calling a global function with example usage: check_gpu_support() and returns: True, False, False