def METHOD_NAME() -> None:
    def make_graph(
        node: onnx.helper.NodeProto,
        input_shape: Sequence[int],
        output_shape: Sequence[int],
    ) -> onnx.helper.GraphProto:
        graph = onnx.helper.make_graph(
            nodes=[node],
            name="StringNormalizer",
            inputs=[
                onnx.helper.make_tensor_value_info(
                    "x", onnx.TensorProto.STRING, input_shape
                )
            ],
            outputs=[
                onnx.helper.make_tensor_value_info(
                    "y", onnx.TensorProto.STRING, output_shape
                )
            ],
        )
        return graph
    # 1st model_monday_casesensintive_nochangecase
    stopwords = ["monday"]
    node = onnx.helper.make_node(
        "StringNormalizer",
        inputs=["x"],
        outputs=["y"],
        is_case_sensitive=1,
        stopwords=stopwords,
    )
    x = np.array(["monday", "tuesday", "wednesday", "thursday"]).astype(object)
    y = np.array(["tuesday", "wednesday", "thursday"]).astype(object)
    graph = make_graph(node, [4], [3])
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_monday_casesensintive_nochangecase",
    )
    # 2nd model_nostopwords_nochangecase
    node = onnx.helper.make_node(
        "StringNormalizer", inputs=["x"], outputs=["y"], is_case_sensitive=1
    )
    x = np.array(["monday", "tuesday"]).astype(object)
    y = x
    graph = make_graph(node, [2], [2])
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_nostopwords_nochangecase",
    )
    # 3rd model_monday_casesensintive_lower
    stopwords = ["monday"]
    node = onnx.helper.make_node(
        "StringNormalizer",
        inputs=["x"],
        outputs=["y"],
        case_change_action="LOWER",
        is_case_sensitive=1,
        stopwords=stopwords,
    )
    x = np.array(["monday", "tuesday", "wednesday", "thursday"]).astype(object)
    y = np.array(["tuesday", "wednesday", "thursday"]).astype(object)
    graph = make_graph(node, [4], [3])
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_monday_casesensintive_lower",
    )
    # 4 model_monday_casesensintive_upper
    stopwords = ["monday"]
    node = onnx.helper.make_node(
        "StringNormalizer",
        inputs=["x"],
        outputs=["y"],
        case_change_action="UPPER",
        is_case_sensitive=1,
        stopwords=stopwords,
    )
    x = np.array(["monday", "tuesday", "wednesday", "thursday"]).astype(object)
    y = np.array(["TUESDAY", "WEDNESDAY", "THURSDAY"]).astype(object)
    graph = make_graph(node, [4], [3])
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_monday_casesensintive_upper",
    )
    # 5 monday_insensintive_upper_twodim
    stopwords = ["monday"]
    node = onnx.helper.make_node(
        "StringNormalizer",
        inputs=["x"],
        outputs=["y"],
        case_change_action="UPPER",
        stopwords=stopwords,
    )
    input_shape = [1, 6]
    output_shape = [1, 4]
    x = (
        np.array(
            ["Monday", "tuesday", "wednesday", "Monday", "tuesday", "wednesday"]
        )
        .astype(object)
        .reshape(input_shape)
    )
    y = (
        np.array(["TUESDAY", "WEDNESDAY", "TUESDAY", "WEDNESDAY"])
        .astype(object)
        .reshape(output_shape)
    )
    graph = make_graph(node, input_shape, output_shape)
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_monday_insensintive_upper_twodim",
    )
    # 6 monday_empty_output
    stopwords = ["monday"]
    node = onnx.helper.make_node(
        "StringNormalizer",
        inputs=["x"],
        outputs=["y"],
        case_change_action="UPPER",
        is_case_sensitive=0,
        stopwords=stopwords,
    )
    x = np.array(["monday", "monday"]).astype(object)
    y = np.array([""]).astype(object)
    graph = make_graph(node, [2], [1])
    model = onnx.helper.make_model_gen_version(
        graph,
        producer_name="backend-test",
        opset_imports=[onnx.helper.make_opsetid("", 10)],
    )
    expect(
        model,
        inputs=[x],
        outputs=[y],
        name="test_strnorm_model_monday_empty_output",
    )