class_docstr: Simple Interaction Network
  One Layer interaction network for stellar multi-body problem simulation,
  it has the ability to simulate number of body motion no more than 12
  Parameters
  ==========
  node_feats : int
      Number of node features
  
  stat : dict
      Statistcics for Denormalization
class_docstr_tok: ["Simple","Interaction","Network","One","Layer","interaction","network","for","stellar","multi-body","problem","simulation",",","it","has","the","ability","to","simulate","number","of","body","motion","no","more","than","12","Parameters","==========","node_feats",":","int","Number","of","node","features","stat",":","dict","Statistcics","for","Denormalization"]
code: def denormalize_output(self, out):
      return (
          out * (self.stat["max"][3:5] - self.stat["min"][3:5]) / 2
          + self.stat["median"][3:5]
      )
  
imports: import copy
  from functools import partial
  import dgl
  import dgl.function
  import dgl.nn
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the InteractionNet obj's underlying member method code with example usage: obj.denormalize_output(out) and returns: unknown