code: def construct_pre_processing_matrix_adj_bar() -> (
      Tuple[torch.Tensor, torch.Tensor]
  ):
      """Construct the test input, and output matrix
  
      :return: Return the input and output matrix for adjacency matrix pre-processing
      """
      in_matrix = torch.tensor(
          [
              [0, 0, 0, 0, 1],
              [0, 0, 0, 1, 1],
              [0, 0, 0, 1, 1],
              [0, 1, 1, 0, 1],
              [1, 1, 1, 1, 0],
          ]
      )
  
      result_matrix = in_matrix + torch.eye(in_matrix.shape[0])
  
      return in_matrix, result_matrix
  
file_path: maze/maze/test/perception/blocks/test_graph_attention.py
imports: from typing import Dict, Tuple
  import torch
  import torch.nn
  from maze.perception.blocks.feed_forward.graph_attention import GraphAttentionBlock, GraphAttentionLayer, GraphMultiHeadAttentionLayer
  from maze.perception.weight_init import make_module_init_normc
  from maze.test.perception.perception_test_utils import build_input_dict
label_desc: Use image node_id 1 for calling a global function with example usage: construct_pre_processing_matrix_adj_bar() and returns: in_matrix,  result_matrix