code: def test_valid_deployment_target_cumsum(self, target):
      x_shape = (3, 4, 5)
  
      @make_tf_graph([x_shape])
      def build_model(x):
          return tf.math.cumsum(
              x, axis=-1, reverse=False, exclusive=False
          )
  
      model, inputs, outputs = build_model
  
      # successful conversion
      converter.convert(model, minimum_deployment_target=target)
  
imports: import os
  import shutil
  import tempfile
  import numpy
  import pytest
  import coremltools
  import coremltools.converters
  import coremltools.proto.FeatureTypes_pb2
  from coremltools import EnumeratedShapes, ImageType, RangeDim, TensorType
  from coremltools._deps import _HAS_TF_1, _IS_MACOS, MSG_TF1_NOT_FOUND
  from coremltools.converters.mil.frontend.tensorflow.converter import TFConverter
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import TensorFlowBaseTest, get_tf_keras_io_names, make_tf_graph
  from coremltools.converters.mil.testing_reqs import backends
  from coremltools.converters.mil.testing_utils import random_gen
label_desc: Use image node_id 10 for calling the TestTfModelInputsOutputs obj's underlying member method code with example usage: obj.test_valid_deployment_target_cumsum(target) and returns: tf