def METHOD_NAME(hmeq_dataset):
    """
    Test Cases:
    - no score code
    - Viya 4
    - Viya 3.5
    """
    model_files = {
        "Test.json": {"Test": True, "TestNum": 1},
        "Other_Test.json": {"Other": None, "TestNum": 2},
        "ModelProperties.json": {"Model": "Test"},
        "inputVar.json": [
            {"name": "LOAN", "level": "interval", "type": "decimal", "length": 8},
            {
                "name": "MORTDUE",
                "level": "interval",
                "type": "decimal",
                "length": 8,
            },
            {"name": "VALUE", "level": "interval", "type": "decimal", "length": 8},
            {"name": "YOJ", "level": "interval", "type": "decimal", "length": 8},
            {"name": "DEROG", "level": "interval", "type": "decimal", "length": 8},
            {"name": "DELINQ", "level": "interval", "type": "decimal", "length": 8},
            {"name": "CLAGE", "level": "interval", "type": "decimal", "length": 8},
            {"name": "NINQ", "level": "interval", "type": "decimal", "length": 8},
            {"name": "CLNO", "level": "interval", "type": "decimal", "length": 8},
            {
                "name": "DEBTINC",
                "level": "interval",
                "type": "decimal",
                "length": 8,
            },
        ],
        "outputVar.json": [
            {
                "name": "Classification",
                "level": "nominal",
                "type": "string",
                "length": 1,
            },
            {
                "name": "Probability",
                "level": "interval",
                "type": "decimal",
                "length": 8,
            },
        ],
    }
    model, model_files = im.import_model(
        model_files, "No_Score_Model", "Test_Project", overwrite_model=True
    )
    assert model == mr.get_model(model)
    for file in mr.get_model_contents(model):
        assert file.name in [
            "Test.json",
            "Other_Test.json",
            "ModelProperties.json",
            "inputVar.json",
            "outputVar.json",
        ]
    input_data = hmeq_dataset.drop(columns=["BAD", "REASON", "JOB"])
    output_vars = ["Classification", "Probability"]
    if current_session().version_info() == 4:
        model, model_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            input_data=input_data,
            predict_method=[fake_predict, [int, int]],
            score_metrics=output_vars,
            binary_string=b"Test Binary String",
            overwrite_model=True,
        )
        assert model == mr.get_model(model)
        for file in mr.get_model_contents(model):
            assert file.name in [
                "Test.json",
                "Other_Test.json",
                "inputVar.json",
                "ModelProperties.json",
                "outputVar.json",
                "score_Test_Model.py",
            ]
    else:
        model, model_files = im.import_model(
            model_files,
            "Test_Model",
            "Test_Project",
            input_data=input_data,
            predict_method=[fake_predict, [int, int]],
            score_metrics=output_vars,
            binary_string=b"Test Binary String",
            overwrite_model=True,
        )
        assert model == mr.get_model(model)
        for file in mr.get_model_contents(model):
            file_list = [
                "Test.json",
                "Other_Test.json",
                "score_Test_Model.py",
                "ModelProperties.json",
                "inputVar.json",
                "outputVar.json",
                "score.sas",
                "dmcas_epscorecode.sas",
                "dmcas_packagescorecode.sas",
            ]
            assert file.name in file_list