code: def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
      init_parameters = inspect.signature(profiler.__init__).parameters
      kwargs = {
          k: v
          for k, v in self._profiler_kwargs.items()
          if k in init_parameters
      }
      return profiler(**kwargs)
  
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 11 for calling the PyTorchProfiler obj's underlying member method code with example usage: obj._create_profiler(profiler) and returns: profiler