code: def aggregate_min(h):
      """min aggregation"""
      return torch.min(h, dim=1)[0]
  
imports: from typing import List
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.nn import AvgPooling, SumPooling
  from ogb.graphproppred.mol_encoder import AtomEncoder
label_desc: Use image node_id 3 for calling a global function with example usage: aggregate_min(h) and returns: torch