code: def get_nonlinear(nonlinear):
      nonlinear_func_dict = {
          "relu": F.relu,
          "leakyrelu": partial(F.leaky_relu, negative_slope=0.2),
          "sigmoid": F.sigmoid,
          "elu": F.elu,
      }
      return nonlinear_func_dict[nonlinear]
  
imports: import torch
  import torch.nn
  from functools import partial
  from typing import Union, List
  import torch.nn.functional
  from torch_geometric.data import Batch
  from torch_geometric.nn.conv.gcn_conv import gcn_norm
  from torch_geometric.nn.conv import GCNConv
  from torch_geometric.nn.glob import global_mean_pool, global_add_pool, global_max_pool
  from torch import Tensor
  from torch_sparse import SparseTensor, fill_diag
  from torch_geometric.typing import Adj, OptTensor, Size
  from torch_geometric.utils import add_self_loops
  from dig.xgraph.models import GNNPool
  from collections import OrderedDict
label_desc: Use image node_id 5 for calling a global function with example usage: get_nonlinear(nonlinear) and returns: nonlinear_func_dict