code: def set_allocators():
      import rmm
      import cudf
      import cupy
      from rmm.allocators.torch import rmm_torch_allocator
      from rmm.allocators.cupy import rmm_cupy_allocator
  
      mr = rmm.mr.CudaAsyncMemoryResource()
      rmm.mr.set_current_device_resource(mr)
      torch.cuda.memory.change_current_allocator(rmm_torch_allocator)
      cupy.cuda.set_allocator(rmm_cupy_allocator)
      cudf.set_option("spill", True)
  
imports: import warnings
  import time
  import cugraph_dgl
  import torch
  import torch.nn
  import torch.nn.functional
  import torchmetrics.functional
  import dgl
  import dgl.nn
  from dgl.data import AsNodePredDataset
  from dgl.dataloading import DataLoader, NeighborSampler, MultiLayerFullNeighborSampler
  from ogb.nodeproppred import DglNodePropPredDataset
  import tqdm
  import argparse
label_desc: Use image node_id 1 for calling a global function with example usage: set_allocators() without return types