diff --git a/framework/api/paddlebase/test_nonzero.py b/framework/api/paddlebase/test_nonzero.py index 88eaf635ac..d24be27c9c 100644 --- a/framework/api/paddlebase/test_nonzero.py +++ b/framework/api/paddlebase/test_nonzero.py @@ -64,12 +64,10 @@ def test_nonzero2(): x = paddle.to_tensor(np.array([[1.0, 1.0, 4.0], [0.0, 2.0, 0.0], [0.0, 0.0, 3.0]]).astype(np.float32)) as_tuple_ = True outputs = paddle.nonzero(x, as_tuple_) - res = np.array([ - [0, 0, 0, 1, 2], - [0, 1, 2, 1, 2] - ]).astype(np.int64) - outputs_np = np.stack([i.numpy() for i in outputs], axis=0) - npt.assert_allclose(outputs_np, res) + res = np.array([[[0], [0], [0], [1], [2]], [[0], [1], [2], [1], [2]]]).astype(np.int64) + for i in range(outputs.__len__()): + out = outputs[i].numpy() + npt.assert_allclose(out, res[i, :, :]) @pytest.mark.api_base_nonzero_parameters @@ -94,9 +92,10 @@ def test_nonzero4(): x = paddle.to_tensor(np.array([2, 1, 0, 3]).astype(np.int32)) as_tuple_ = True outputs = paddle.nonzero(x, as_tuple_) - res = np.array([[0, 1, 3]]).astype(np.int64) - outputs_np = np.stack([i.numpy() for i in outputs], axis=0) - npt.assert_allclose(outputs_np, res) + res = np.array([[[0], [1], [3]]]).astype(np.int64) + for i in range(outputs.__len__()): + out = outputs[i].numpy() + npt.assert_allclose(out, res[i, :]) @pytest.mark.api_base_nonzero_parameters @@ -154,11 +153,12 @@ def test_nonzero6(): outputs = paddle.nonzero(x, as_tuple_) res = np.array( [ - [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2], - [0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1], - [0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1], - [0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1] + [[0.0], [0.0], [0.0], [0.0], [0.0], [1.0], [1.0], [1.0], [1.0], [1.0], [1.0], [2.0], [2.0], [2.0], [2.0]], + [[0.0], [0.0], [1.0], [1.0], [1.0], [0.0], [0.0], [0.0], [1.0], [1.0], [1.0], [0.0], [1.0], [1.0], [1.0]], + [[0.0], [0.0], [0.0], [1.0], [1.0], [0.0], [0.0], [1.0], [0.0], [1.0], [1.0], [0.0], [0.0], [1.0], [1.0]], + [[0.0], [1.0], [0.0], [0.0], [1.0], [0.0], [1.0], [1.0], [0.0], [0.0], [1.0], [0.0], [1.0], [0.0], [1.0]], ] ).astype(np.int64) - outputs_np = np.stack([i.numpy() for i in outputs], axis=0) - npt.assert_allclose(outputs_np, res) + for i in range(outputs.__len__()): + out = outputs[i].numpy() + npt.assert_allclose(out, res[i, :, :])