class_docstr: triton matmul kernel superclass
code: def _update_autotune_table(cache_key, triton_kernel):
      cache_manager = AutotuneCacheManager(cache_key)
      autotune_table = cache_manager.load()
      if autotune_table is None:
          autotune_table = dict()
      autotune_table.update(
          triton_kernel.cache
      )  # always overwrite with the new autotune results
      cache_manager = AutotuneCacheManager(cache_key)
      cache_manager.put(autotune_table)
  
imports: import torch
  import triton
  import os
  from filelock import FileLock
  import deepspeed.ops.transformer.inference.triton.triton_matmul_kernel
  import pickle
  from io import open
  import deepspeed
  from pathlib import Path
  import atexit
label_desc: Use image node_id 5 for calling the TritonMatmul obj's underlying member method code with example usage: obj._update_autotune_table(cache_key, triton_kernel) without return types