code: def _get_num_processes(accelerator: str, devices: str) -> int:
      """Parse the `devices` argument to determine how many processes need to be launched on the current machine."""
      if accelerator == "gpu":
          parsed_devices = _parse_gpu_ids(
              devices, include_cuda=True, include_mps=True
          )
      elif accelerator == "cuda":
          parsed_devices = CUDAAccelerator.parse_devices(devices)
      elif accelerator == "mps":
          parsed_devices = MPSAccelerator.parse_devices(devices)
      elif accelerator == "tpu":
          raise ValueError(
              "Launching processes for TPU through the CLI is not supported."
          )
      else:
          return CPUAccelerator.parse_devices(devices)
      return len(parsed_devices) if parsed_devices is not None else 0
  
file_path: pytorch-lightning/src/lightning/fabric/cli.py
imports: import logging
  import os
  import re
  from argparse import Namespace
  from typing import Any, List, Optional
  from lightning_utilities.core.imports import RequirementCache
  from typing_extensions import get_args
  from lightning.fabric.accelerators import CPUAccelerator, CUDAAccelerator, MPSAccelerator
  from lightning.fabric.plugins.precision.precision import _PRECISION_INPUT_STR, _PRECISION_INPUT_STR_ALIAS
  from lightning.fabric.strategies import STRATEGY_REGISTRY
  from lightning.fabric.utilities.device_parser import _parse_gpu_ids
  from lightning.fabric.utilities.distributed import _suggested_max_num_threads
label_desc: Use image node_id 3 for calling a global function with example usage: _get_num_processes(accelerator, devices) and returns: unknown, CPUAccelerator