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- adj_k_prob = adj_prob
- for i in range(K):
- adj_k_prob += np.matmul(adj_prob, adj_k_prob)
- adj_k_prob = adj_prob_tensor
- for i in range(K):
- adj_k_prob += torch.matmul(adj_prob_tensor, adj_k_prob)
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