code: def _cache_functions_events(self) -> None:
      if self._emit_nvtx:
          return
  
      if _KINETO_AVAILABLE:
          assert isinstance(self.profiler, torch.profiler.profile)
          self.function_events = self.profiler.events()
      else:
          assert isinstance(
              self.profiler, torch.autograd.profiler.profile
          )
          self.function_events = self.profiler.function_events
  
imports: import inspect
  import logging
  import os
  from functools import lru_cache, partial
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Callable, ContextManager, Dict, List, Optional, Type, Union
  import torch
  from torch import Tensor, nn
  from torch.autograd.profiler import EventList, record_function
  from torch.profiler import ProfilerAction, ProfilerActivity, tensorboard_trace_handler
  from torch.utils.hooks import RemovableHandle
  from typing_extensions import override
  from lightning.fabric.accelerators.cuda import is_cuda_available
  from lightning.pytorch.profilers.profiler import Profiler
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.rank_zero import WarningCache, rank_zero_warn
label_desc: Use image node_id 12 for calling the PyTorchProfiler obj's underlying member method code with example usage: obj._cache_functions_events() without return types