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 math
  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