code: def check_pytorch_version() -> None:
      if torch_version() < (1, 8, 0):
          raise Exception(
              "DistributedPipeline requires PyTorch version 1.8 or higher"
          )
  
file_path: fairscale/fairscale/experimental/nn/distributed_pipeline/pipeline.py
imports: from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Union
  import torch
  from torch import Tensor, nn
  from torch.distributed import rpc
  from fairscale.internal import torch_version
  from fairscale.nn.pipe import microbatch
  from .data import DataConsumer
  from .graph import Node, PipelineModulesGraph
  from .partition_handler import DistributedPipelineRecord, PartitionHandler
label_desc: Use image node_id 1 for calling a global function with example usage: check_pytorch_version() without return types