code: def setup_fsdp_envs(cfg):
      os.environ["ACCELERATE_USE_FSDP"] = "true"
      if cfg.fsdp_config.fsdp_offload_params:
          os.environ["FSDP_OFFLOAD_PARAMS"] = "true"
      if cfg.fsdp_config.fsdp_sync_module_states:
          os.environ["FSDP_SYNC_MODULE_STATES"] = "true"
      if cfg.fsdp_config.fsdp_state_dict_type:
          os.environ[
              "FSDP_STATE_DICT_TYPE"
          ] = cfg.fsdp_config.fsdp_state_dict_type
      if cfg.fsdp_config.fsdp_transformer_layer_cls_to_wrap:
          os.environ[
              "FSDP_TRANSFORMER_CLS_TO_WRAP"
          ] = cfg.fsdp_config.fsdp_transformer_layer_cls_to_wrap
  
imports: import math
  import os
  from contextlib import contextmanager
  from functools import partial
  from typing import List
  import numpy
  import torch
  import torch.cuda
  from accelerate.logging import get_logger
  from datasets import set_caching_enabled
  from torch.utils.data import DataLoader, RandomSampler
  from axolotl.core.trainer_builder import HFCausalTrainerBuilder, HFDPOTrainerBuilder
  from axolotl.utils.distributed import is_main_process, reduce_and_broadcast, zero_first
  from axolotl.utils.samplers import MultipackBatchSampler, get_dataset_lengths
label_desc: Use image node_id 11 for calling a global function with example usage: setup_fsdp_envs(cfg) without return types