class_docstr: Interface for message passing layer to be used in graph neural networks with multiple edge types.
class_docstr_tok: ["Interface","for","message","passing","layer","to","be","used","in","graph","neural","networks","with","multiple","edge","types","."]
code: def output_state_dimension(self) -> int:
      pass
  
file_path: ptgnn/ptgnn/neuralmodels/gnn/messagepassing/abstractmessagepassing.py
imports: import torch
  from abc import abstractmethod
  from torch import nn
  from torch_scatter import scatter
  from typing import Dict, List, Tuple
label_desc: Use image node_id 4 for calling the AbstractMessagePassingLayer obj's underlying member method code with example usage: obj.output_state_dimension() without return types