code: def get_readout_layers(readout):
      readout_func_dict = {
          "mean": global_mean_pool,
          "sum": global_add_pool,
          "max": global_max_pool,
          "identity": identity,
          "cat_max_sum": cat_max_sum,
      }
      readout_func_dict = {
          k.lower(): v for k, v in readout_func_dict.items()
      }
      return readout_func_dict[readout.lower()]
  
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 4 for calling a global function with example usage: get_readout_layers(readout) and returns: readout_func_dict