class_docstr: Principal Neighbourhood Aggregation for Graph Nets
  
  https://arxiv.org/abs/2004.05718
class_docstr_tok: ["Principal","Neighbourhood","Aggregation","for","Graph","Nets","https",":","\/\/arxiv.org\/abs\/2004.05718"]
code: def __init__(
      self,
      delta: float = 1,
  ):
      super().__init__()
      self._delta = delta
  
file_path: ptgnn/ptgnn/neuralmodels/gnn/messagepassing/pna_aggregation.py
imports: import torch
  from torch import nn
  from torch_scatter import scatter
  from typing import Dict, List, Optional, Tuple, Union
  from ptgnn.neuralmodels.gnn.messagepassing.abstractmessagepassing import AbstractMessageAggregation, AbstractMessagePassingLayer
  from ptgnn.neuralmodels.mlp import MLP
label_desc: Use image node_id 1 to create a new PnaMessageAggregation object from inherited base classes: AbstractMessageAggregation with example: obj = PnaMessageAggregation(delta)