code: def testSplitTensorValueSparseTypesPreserved(self):
      split_tensor_values = util.split_tensor_value(
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0], [0, 1], [2, 0], [3, 1]]),
              values=np.array(
                  ["zero0", "zero1", "two0", "three1"], dtype=object
              ),
              dense_shape=np.array([4, 3]),
          )
      )
      expected_sparse_tensor_values = [
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0], [0, 1]]),
              values=np.array(["zero0", "zero1"], dtype=object),
              dense_shape=np.array([1, 2]),
          ),
          tf.compat.v1.SparseTensorValue(
              indices=np.zeros([0, 2], dtype=np.int64),
              values=np.zeros([0], dtype=object),
              dense_shape=np.array([1, 0]),
          ),
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0]]),
              values=np.array(["two0"], dtype=object),
              dense_shape=np.array([1, 1]),
          ),
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 1]]),
              values=np.array(["three1"], dtype=object),
              dense_shape=np.array([1, 2]),
          ),
      ]
      for expected_sparse_tensor_value, got_sparse_tensor_value in zip(
          expected_sparse_tensor_values, split_tensor_values
      ):
          self.assertSparseTensorValueEqual(
              expected_sparse_tensor_value, got_sparse_tensor_value
          )
  
file_path: model-analysis/tensorflow_model_analysis/eval_saved_model/util_test.py
imports: import numpy
  import tensorflow
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.eval_saved_model import util
  from tensorflow.core.example import example_pb2
label_desc: Use image node_id 6 for calling the UtilTest obj's underlying member method code with example usage: obj.testSplitTensorValueSparseTypesPreserved() without return types