code: def cat_max_sum(x, batch):
      node_dim = x.shape[-1]
      num_node = 25
      x = x.reshape(-1, num_node, node_dim)
      return torch.cat([x.max(dim=1)[0], x.sum(dim=1)], dim=-1)
  
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 3 for calling a global function with example usage: cat_max_sum(x, batch) and returns: torch