Function check_out

test/test_models.py:739–757

(out)

        out = model(x)

    def check_out(out):
        prec = 0.01
        try:
            # We first try to assert the entire output if possible. This is not
            # only the best way to assert results but also handles the cases
            # where we need to create a new expected result.
            _assert_expected(out.cpu(), model_name, prec=prec)
        except AssertionError:
            # Unfortunately some segmentation models are flaky with autocast
            # so instead of validating the probability scores, check that the class
            # predictions match.
            expected_file = _get_expected_file(model_name)
            expected = torch.load(expected_file, weights_only=True)
            torch.testing.assert_close(
                out.argmax(dim=1), expected.argmax(dim=1), rtol=prec, atol=prec, check_device=False
            )
            return False  # Partial validation performed

        return True  # Full validation performed

    full_validation = check_out(out["out"])