code: def delete_cache(self, t, j, k):
      v = self.cache_home[t][j][k].pop()
      if v:
          for x in v:
              x.delete()
  
imports: import argparse
  from itertools import count
  import os
  import pickle
  import traceback
  from typing import Union, List, Optional
  import numpy
  import torch
  import torch.distributed
  from transformers import AutoTokenizer
  from flexgen.compression import CompressionConfig
  from flexgen.dist_utils import initialize_distributed
  from flexgen.flex_opt import Policy, InputEmbed, OutputEmbed, SelfAttention, MLP, TransformerLayer, OptLM, get_filename, add_parser_arguments, get_test_inputs, DUMMY_WEIGHT
  from flexgen.opt_config import get_opt_config
  from flexgen.pytorch_backend import TorchDevice, TorchDisk, TorchLink, TorchMixedDevice, TorchTensor
  from flexgen.timer import timers
  from flexgen.utils import Task, ExecutionEnv, GB, T, ValueHolder, array_1d, array_2d, array_3d, array_4d, str2bool, project_decode_latency
label_desc: Use image node_id 6 for calling the DistOptLM obj's underlying member method code with example usage: obj.delete_cache(t, j, k) without return types