def METHOD_NAME():
    paddle.set_device("cpu")
    model_torch = PTBertForMaskedLM.from_pretrained("./bert-base-uncased")
    model_paddle = PDBertForMaskedLM.from_pretrained("./bert-base-uncased")
    model_torch.eval()
    model_paddle.eval()
    np.random.seed(42)
    x = np.random.randint(1, model_paddle.bert.config["vocab_size"], size=(4, 64))
    input_torch = torch.tensor(x, dtype=torch.int64)
    out_torch = model_torch(input_torch)[0]
    input_paddle = paddle.to_tensor(x, dtype=paddle.int64)
    out_paddle = model_paddle(input_paddle)[0]
    print("torch result shape:{}".format(out_torch.shape))
    print("paddle result shape:{}".format(out_paddle.shape))
    compare(out_torch, out_paddle)