blob: 76c9c3b336bdc1d2a07b3d47c720787098be7713 [file] [log] [blame]
# Owner(s): ["module: onnx"]
import torch
from torch.onnx import _experimental, verification
from torch.testing._internal import common_utils
class TestVerification(common_utils.TestCase):
def setUp(self) -> None:
super().setUp()
torch.manual_seed(0)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(0)
def test_check_export_model_diff_returns_diff_when_constant_mismatch(self):
class UnexportableModel(torch.nn.Module):
def forward(self, x, y):
# tensor.data() will be exported as a constant,
# leading to wrong model output under different inputs.
return x + y.data
test_input_groups = [
((torch.randn(2, 3), torch.randn(2, 3)), {}),
((torch.randn(2, 3), torch.randn(2, 3)), {}),
]
results = verification.check_export_model_diff(
UnexportableModel(), test_input_groups
)
self.assertRegex(
results,
r"Graph diff:(.|\n)*"
r"First diverging operator:(.|\n)*"
r"prim::Constant(.|\n)*"
r"Former source location:(.|\n)*"
r"Latter source location:",
)
def test_check_export_model_diff_returns_diff_when_dynamic_controlflow_mismatch(
self,
):
class UnexportableModel(torch.nn.Module):
def forward(self, x, y):
for i in range(x.size(0)):
y = x[i] + y
return y
test_input_groups = [
((torch.randn(2, 3), torch.randn(2, 3)), {}),
((torch.randn(4, 3), torch.randn(2, 3)), {}),
]
export_options = _experimental.ExportOptions(
input_names=["x", "y"], dynamic_axes={"x": [0]}
)
results = verification.check_export_model_diff(
UnexportableModel(), test_input_groups, export_options
)
self.assertRegex(
results,
r"Graph diff:(.|\n)*"
r"First diverging operator:(.|\n)*"
r"prim::Constant(.|\n)*"
r"Latter source location:(.|\n)*",
)
def test_check_export_model_diff_returns_empty_when_correct_export(self):
class SupportedModel(torch.nn.Module):
def forward(self, x, y):
return x + y
test_input_groups = [
((torch.randn(2, 3), torch.randn(2, 3)), {}),
((torch.randn(2, 3), torch.randn(2, 3)), {}),
]
results = verification.check_export_model_diff(
SupportedModel(), test_input_groups
)
self.assertEqual(results, "")