code: def _get_cuda_device_if_available():
      if torch.cuda.is_available():
          return torch.device("cuda")
      else:
          return torch.device("cpu")
  
imports: from abc import abstractmethod
  import numpy
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.validation import check_X_y, assert_all_finite, check_array, check_is_fitted
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 2 for calling a global function with example usage: _get_cuda_device_if_available() and returns: torch, torch