From 2307b9dd394029ed854b7d710d5b3740e4ad04d5 Mon Sep 17 00:00:00 2001 From: hedongdong Date: Sat, 4 Feb 2023 17:23:11 +0800 Subject: [PATCH] fix testcase for gpu op of hswish --- tests/st/ops/gpu/test_hswish_op.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/tests/st/ops/gpu/test_hswish_op.py b/tests/st/ops/gpu/test_hswish_op.py index 7de5f6a7b39..3c8f5b4e174 100644 --- a/tests/st/ops/gpu/test_hswish_op.py +++ b/tests/st/ops/gpu/test_hswish_op.py @@ -47,28 +47,28 @@ def expect_hswish_forward_result(x): def expect_hswish_backward_result(x, dout): - return np.where(x <= -3, 0, np.where(x >= 3, 1, x / 3 + 0.5)) * dout + return np.where(x <= -3, 0, np.where(x >= 3, 1, (x * 2 + 3) / 6)) * dout -def judge_result_correct(result, expect): +def judge_result_correct(result, expect, loss): assert result.dtype == expect.dtype assert result.shape == expect.shape - assert np.allclose(result, expect) + assert np.allclose(result, expect, loss, loss) -def generate_test_cases(np_type, mode): +def generate_test_cases(np_type, mode, loss): context.set_context(mode=mode, device_target="GPU") x = np.array([-1, -2, 0, 4, 5]).astype(np_type) net = Net() output = net(Tensor(x)) expect = expect_hswish_forward_result(x) - judge_result_correct(output.asnumpy(), expect) + judge_result_correct(output.asnumpy(), expect, loss) sens = np.array([-1.45, 0.63, 0.34, 6.43, 34.6]).astype(np_type) backward_net = Grad(Net()) output = backward_net(Tensor(x), Tensor(sens)) expect = expect_hswish_backward_result(x, sens) - judge_result_correct(output[0].asnumpy(), expect) + judge_result_correct(output[0].asnumpy(), expect, loss) @pytest.mark.level1 @@ -79,4 +79,5 @@ def test_hswish_forward_and_backward(): dtypes = (np.float32, np.float16) for mode in modes: for dtype in dtypes: - generate_test_cases(dtype, mode) + loss = 1e-4 if (dtype == np.float32) else 1e-3 + generate_test_cases(dtype, mode, loss)