code: def sign_diffusion(A, X, r):
      # Perform the r-hop diffusion operation.
      X_sign = [X]
      for _ in range(r):
          X = A @ X
          X_sign.append(X)
      return X_sign
  
file_path: dgl/examples/sparse/sign.py
imports: import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import CoraGraphDataset
  from torch.optim import Adam
label_desc: Use image node_id 1 for calling a global function with example usage: sign_diffusion(A, X, r) and returns: X_sign