code: def label_propagation(A_hat, label, num_layers=20, alpha=0.9):
      Y = label
      for _ in range(num_layers):
          Y = alpha * A_hat @ Y + (1 - alpha) * label
          Y = Y.clamp_(0.0, 1.0)
      return Y
  
file_path: dgl/examples/sparse/c_and_s.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: label_propagation(A_hat, label, num_layers, alpha) and returns: Y