code: def maybe_flush_pytorch_cache(chance: float = 1.0):
      """Flip a coin and decide whether to flush PyTorch's cache. This allows the
      cache to be flushed periodically without maintaining a counter.
  
      I'm not sure why this is necessary, it shouldn't be. But it definitely does
      help...
      """
      if random.random() < chance and torch.cuda.is_available():
          torch.cuda.empty_cache()
  
imports: from typing import List, Dict, Union, Set
  from pathlib import Path
  import random
  from transformers import AutoModel, AutoTokenizer
  from transformers.tokenization_utils import BatchEncoding
  from transformers.tokenization_utils_fast import PreTrainedTokenizerFast
  import catalogue
  from spacy.util import registry
  from thinc.api import get_torch_default_device
  import torch.cuda
  import tempfile
  import shutil
  import contextlib
  import warnings
label_desc: Use image node_id 3 for calling a global function with example usage: maybe_flush_pytorch_cache(chance) without return types