def METHOD_NAME(mock_import, mock_project, mock_score):
    """
    Test Cases:
    - mlflow models set pickle type
    - no score code generation
    - viya 4
        - in memory files
        - disk files
        - error for failed upload
    - viya 3.5
        - in memory files
        - disk files
        - error for failed upload
    """
    with patch("sasctl.core.Session._get_authorization_token"):
        current_session("example.com", "user", "password")
    with patch("sasctl.core.Session.version_info") as mock_version:
        mock_version.return_value = VersionInfo(4)
        mock_project.return_value = None
        mock_score.return_value = {
            "Test_Model_score.py": f"import sasctl\ndef score():\n{'':4}return \"Test\""
        }
        mock_import.return_value = {"name": "Test_Model", "id": "abcdef"}
        model_files = {
            "Test.json": json.dumps({"Test": True, "TestNum": 1}),
            "Other_Test.json": json.dumps({"Other": None, "TestNum": 2}),
        }
        with pytest.warns():
            model, return_files = im.import_model(
                model_files, "Test_Model", "Test_Project"
            )
        model, return_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            pd.DataFrame(data=[[1, 1]]),
            _fake_predict,
            ["C", "P"],
            mlflow_details={"serialization_format": "dill"},
        )
        _, _, kwargs = mock_score.mock_calls[0]
        assert ("pickle_type", "dill") in kwargs.items()
        assert isinstance(return_files, dict)
        mock_version.return_value = VersionInfo(3)
        model, return_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            pd.DataFrame(data=[[1, 1]]),
            _fake_predict,
            ["C", "P"],
        )
        assert isinstance(return_files, dict)
        tmp_dir = tempfile.TemporaryDirectory()
        _ = tempfile.NamedTemporaryFile(delete=False, suffix=".json", dir=tmp_dir.name)
        model_files = Path(tmp_dir.name)
        mock_score.return_value = None
        model, return_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            pd.DataFrame(data=[[1, 1]]),
            _fake_predict,
            ["C", "P"],
        )
        assert not isinstance(return_files, dict)
        mock_version.return_value = VersionInfo(4)
        model, return_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            pd.DataFrame(data=[[1, 1]]),
            _fake_predict,
            ["C", "P"],
        )
        assert not isinstance(return_files, dict)