code: def all_reduce_mean(tensor: torch.Tensor) -> torch.Tensor:
      dist.all_reduce(tensor, op=dist.ReduceOp.SUM)
      tensor = tensor.data
      tensor.div_(dist.get_world_size())
      return tensor
  
imports: import argparse
  import os
  import resource
  from contextlib import nullcontext
  from functools import partial
  from typing import Optional, Tuple
  import torch
  import torch.distributed
  import torch.nn
  from attn import SUPPORT_XFORMERS, replace_xformers
  from data_utils import load_json, prepare_dataloader, save_json
  from datasets import load_dataset
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.utils.tensorboard import SummaryWriter
  from tqdm import tqdm
  from transformers.models.llama.configuration_llama import LlamaConfig
  from transformers.models.llama.modeling_llama import LlamaForCausalLM
  from transformers.models.llama.tokenization_llama import LlamaTokenizer
  import colossalai
  from colossalai.booster import Booster
  from colossalai.booster.plugin import GeminiPlugin, HybridParallelPlugin, LowLevelZeroPlugin
  from colossalai.cluster import DistCoordinator
  from colossalai.lazy import LazyInitContext
  from colossalai.nn.lr_scheduler import CosineAnnealingWarmupLR
  from colossalai.nn.optimizer import HybridAdam
  from colossalai.utils import get_current_device
label_desc: Use image node_id 4 for calling a global function with example usage: all_reduce_mean(tensor) and returns: tensor