code: def compute_adjacency_matrix_images(coord, feat, use_feat=True):
      coord = coord.reshape(-1, 2)
      # Compute coordinate distance.
      c_dist = cdist(coord, coord)
  
      if use_feat:
          # Compute feature distance.
          f_dist = cdist(feat, feat)
          # Compute adjacency.
          A = np.exp(
              -((c_dist / sigma(c_dist)) ** 2)
              - (f_dist / sigma(f_dist)) ** 2
          )
      else:
          A = np.exp(-((c_dist / sigma(c_dist)) ** 2))
  
      # Convert to symmetric matrix.
      A = 0.5 * (A + A.T)
      A[np.diag_indices_from(A)] = 0
      return A
  
imports: import os
  import pickle
  import numpy
  from scipy.spatial.distance import cdist
  from tqdm import tqdm
  from ..None import backend
  from ..convert import graph
  from .dgl_dataset import DGLDataset
  from .utils import download, extract_archive, load_graphs, save_graphs, Subset
label_desc: Use image node_id 2 for calling a global function with example usage: compute_adjacency_matrix_images(coord, feat, use_feat) and returns: A