code: def _aggregate_moment(h, n):
      """moment aggregation: for each node (E[(X-E[X])^n])^{1/n}"""
      h_mean = torch.mean(h, dim=1, keepdim=True)
      h_n = torch.mean(torch.pow(h - h_mean, n), dim=1)
      rooted_h_n = torch.sign(h_n) * torch.pow(
          torch.abs(h_n) + 1e-30, 1.0 / n
      )
      return rooted_h_n
  
imports: import numpy
  import torch
  import torch.nn
label_desc: Use image node_id 7 for calling a global function with example usage: _aggregate_moment(h, n) and returns: rooted_h_n