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Add opchecks for RoiAlign #8057

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merged 4 commits into from
Oct 23, 2023
Merged

Add opchecks for RoiAlign #8057

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9b1d126
Add opchecks for RoiAlign
NicolasHug Oct 21, 2023
a1dee62
Add xfail test for mps
NicolasHug Oct 23, 2023
d377bd2
Add another xfail
NicolasHug Oct 23, 2023
018b581
Fix formatting
NicolasHug Oct 23, 2023
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13 changes: 12 additions & 1 deletion test/optests_failures_dict.json
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Original file line number Diff line number Diff line change
@@ -1,5 +1,16 @@
{
"_description": "This is a dict containing failures for tests autogenerated by generate_opcheck_tests. For more details, please see https://docs.google.com/document/d/1Pj5HRZvdOq3xpFpbEjUZp2hBovhy7Wnxw14m6lF2154/edit",
"_version": 1,
"data": {}
"data": {
"torchvision::roi_align": {
"TestRoIAlign.test_aot_dispatch_dynamic__test_mps_error_inputs": {
"comment": "RuntimeError: MPS does not support roi_align backward with float16 inputs",
"status": "xfail"
},
"TestRoIAlign.test_autograd_registration__test_mps_error_inputs": {
"comment": "NotImplementedError: autograd_registration_check: NYI devices other than CPU/CUDA, got {'mps'}",
"status": "xfail"
}
}
}
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I'm leaving the mps-related stuff as xfail for now, we can fix them eventually in other PRs.

}
13 changes: 13 additions & 0 deletions test/test_ops.py
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Expand Up @@ -474,6 +474,7 @@ def test_boxes_shape(self):
@pytest.mark.parametrize("x_dtype", (torch.float16, torch.float32, torch.float64)) # , ids=str)
@pytest.mark.parametrize("contiguous", (True, False))
@pytest.mark.parametrize("deterministic", (True, False))
@pytest.mark.opcheck_only_one()
def test_forward(self, device, contiguous, deterministic, aligned, x_dtype, rois_dtype=None):
if deterministic and device == "cpu":
pytest.skip("cpu is always deterministic, don't retest")
Expand All @@ -491,6 +492,7 @@ def test_forward(self, device, contiguous, deterministic, aligned, x_dtype, rois
@pytest.mark.parametrize("deterministic", (True, False))
@pytest.mark.parametrize("x_dtype", (torch.float, torch.half))
@pytest.mark.parametrize("rois_dtype", (torch.float, torch.half))
@pytest.mark.opcheck_only_one()
def test_autocast(self, aligned, deterministic, x_dtype, rois_dtype):
with torch.cuda.amp.autocast():
self.test_forward(
Expand All @@ -506,6 +508,7 @@ def test_autocast(self, aligned, deterministic, x_dtype, rois_dtype):
@pytest.mark.parametrize("device", cpu_and_cuda_and_mps())
@pytest.mark.parametrize("contiguous", (True, False))
@pytest.mark.parametrize("deterministic", (True, False))
@pytest.mark.opcheck_only_one()
def test_backward(self, seed, device, contiguous, deterministic):
if deterministic and device == "cpu":
pytest.skip("cpu is always deterministic, don't retest")
Expand All @@ -520,6 +523,7 @@ def _make_rois(self, img_size, num_imgs, dtype, num_rois=1000):
@pytest.mark.parametrize("aligned", (True, False))
@pytest.mark.parametrize("scale, zero_point", ((1, 0), (2, 10), (0.1, 50)))
@pytest.mark.parametrize("qdtype", (torch.qint8, torch.quint8, torch.qint32))
@pytest.mark.opcheck_only_one()
def test_qroialign(self, aligned, scale, zero_point, qdtype):
"""Make sure quantized version of RoIAlign is close to float version"""
pool_size = 5
Expand Down Expand Up @@ -589,6 +593,15 @@ def test_jit_boxes_list(self):
self._helper_jit_boxes_list(model)


optests.generate_opcheck_tests(
testcase=TestRoIAlign,
namespaces=["torchvision"],
failures_dict_path=os.path.join(os.path.dirname(__file__), "optests_failures_dict.json"),
additional_decorators=[],
test_utils=OPTESTS,
)


class TestPSRoIAlign(RoIOpTester):
mps_backward_atol = 5e-2

Expand Down