docstr: clears cache across potentially multiple devices
docstr_tok: ["clears","cache","across","potentially","multiple","devices"]
code: def clear_cuda_caches(self):
      """clears cache across potentially multiple devices"""
      for i in range(torch.cuda.device_count()):
          with torch.cuda.device(i):
              torch.cuda.empty_cache()
  
imports: import torch
  import json, os, msgpack
  from transformers.utils import logging
  import types
  import inspect
  import copy
  from typing import Optional, List, Callable
  from drugs.inject_mixin import InjectDrugsMixin, MODEL_NAME_MAPPING
  from transformers import GenerationMixin
  from transformers.cache_utils import DynamicCache
  from transformers.generation.utils import LogitsProcessorList, StoppingCriteriaList
  from transformers import AutoTokenizer, TextStreamer, GenerationConfig
  import numpy
  import torch
  import torch.nn.functional
  import hashlib
label_desc: Use image node_id 40 for calling the DRUGS obj's underlying member method code with example usage: obj.clear_cuda_caches() without return types