code: def check_optimizers(optimizers):
      for optim in optimizers:
          bad_optim_type = None
          if isinstance(optim, FP16_Optimizer_general):
              bad_optim_type = "apex.fp16_utils.FP16_Optimizer"
          if isinstance(optim, FP16_Optimizer_for_fused):
              bad_optim_type = "apex.optimizers.FP16_Optimizer"
          if bad_optim_type is not None:
              raise RuntimeError(
                  "An incoming optimizer is an instance of {}. ".format(
                      bad_optim_type
                  )
                  + "The optimizer(s) passed to amp.initialize() must be bare \n"
                  "instances of either ordinary Pytorch optimizers, or Apex fused \n"
                  "optimizers.\n"
              )
  
imports: import collections.abc
  from types import MethodType
  import functools
  import sys
  import warnings
  import numpy
  import torch
  from ._amp_state import _amp_state, warn_or_err
  from .handle import disable_casts
  from .scaler import LossScaler
  from ._process_optimizer import _process_optimizer
  from apex.fp16_utils import convert_network
  from ..fp16_utils import FP16_Optimizer
  from ..contrib.optimizers import FP16_Optimizer
label_desc: Use image node_id 5 for calling a global function with example usage: check_optimizers(optimizers) without return types