def test_clip_aten_fallback_due_exception(self):
def bad_clamp(g, self, min, max):
return _onnx_unsupported("Bad boy!")
class MyClip(torch.nn.Module):
def forward(self, x):
return torch.clamp(x, min=-0.5, max=0.5)
onnx_model = export_to_onnx(
MyClip(),
torch.randn(3, 4, requires_grad=True),
custom_ops=[custom_op("aten::clamp", bad_clamp, 9)],
operator_export_type=OperatorExportTypes.ONNX_ATEN_FALLBACK,
)
self.assertAtenOp(onnx_model, "clamp", "Tensor")
def test_clip_aten_fallback_due_exception(self):
x = torch.randn(3, 4, requires_grad=True)
def bad_clamp(g, self, min, max):
return _onnx_unsupported("Bad boy!")
class MyClip(torch.nn.Module):
def forward(self, x):
return torch.clamp(x, min=-0.5, max=0.5)
f = io.BytesIO()
with custom_op("aten::clamp", bad_clamp, 9):
torch.onnx.export(MyClip(), x, f,
operator_export_type=OperatorExportTypes.ONNX_ATEN_FALLBACK)
onnx_model = onnx.load_from_string(f.getvalue())
self.assertAtenOp(onnx_model, "clamp", "Tensor")
