class_docstr: Performs Deep Sets aggregation in which the elements to aggregate are
  first transformed by a Multi-Layer Perceptron (MLP)
  :math:`\phi_{\mathbf{\Theta}}`, summed, and then transformed by another MLP
  :math:`\rho_{\mathbf{\Theta}}`, as suggested in the `"Graph Neural Networks
  with Adaptive Readouts" <https://arxiv.org/abs/2211.04952>`_ paper.
  
  Args:
      local_nn (torch.nn.Module, optional): The neural network
          :math:`\phi_{\mathbf{\Theta}}`, *e.g.*, defined by
          :class:`torch.nn.Sequential` or
          :class:`torch_geometric.nn.models.MLP`. (default: :obj:`None`)
      global_nn (torch.nn.Module, optional): The neural network
          :math:`\rho_{\mathbf{\Theta}}`, *e.g.*, defined by
          :class:`torch.nn.Sequential` or
          :class:`torch_geometric.nn.models.MLP`. (default: :obj:`None`)
class_docstr_tok: ["Performs","Deep","Sets","aggregation","in","which","the","elements","to","aggregate","are","first","transformed","by","a","Multi-Layer","Perceptron","(","MLP",")",":","math",":","`","\\phi_","{","\\mathbf","{","\\Theta","}","}","`",",","summed",",","and","then","transformed","by","another","MLP",":","math",":","`","\\rho_","{","\\mathbf","{","\\Theta","}","}","`",",","as","suggested","in","the","`","``","Graph","Neural","Networks","with","Adaptive","Readouts","''","<","https",":","\/\/arxiv.org\/abs\/2211.04952",">","`","_","paper",".","Args",":","local_nn","(","torch.nn.Module",",","optional",")",":","The","neural","network",":","math",":","`","\\phi_","{","\\mathbf","{","\\Theta","}","}","`",",","*","e.g",".","*",",","defined","by",":","class",":","`","torch.nn.Sequential","`","or",":","class",":","`","torch_geometric.nn.models.MLP","`",".","(","default",":",":","obj",":","`","None","`",")","global_nn","(","torch.nn.Module",",","optional",")",":","The","neural","network",":","math",":","`","\\rho_","{","\\mathbf","{","\\Theta","}","}","`",",","*","e.g",".","*",",","defined","by",":","class",":","`","torch.nn.Sequential","`","or",":","class",":","`","torch_geometric.nn.models.MLP","`",".","(","default",":",":","obj",":","`","None","`",")"]
code: def reset_parameters(self):
      reset(self.local_nn)
      reset(self.local_mlp)
      reset(self.global_nn)
      reset(self.global_mlp)
  
file_path: pytorch_geometric/torch_geometric/nn/aggr/deep_sets.py
imports: from typing import Optional
  import torch
  from torch import Tensor
  from torch_geometric.nn.aggr import Aggregation
  from torch_geometric.nn.inits import reset
label_desc: Use image node_id 2 for calling the DeepSetsAggregation obj's underlying member method code with example usage: obj.reset_parameters() without return types