code: def testSplitTensorValueSparseVarLen(self):
      split_tensor_values = util.split_tensor_value(
          tf.compat.v1.SparseTensorValue(
              indices=np.array(
                  [
                      [0, 0],
                      [1, 0],
                      [1, 1],
                      [1, 2],
                      [1, 3],
                      [2, 0],
                      [2, 1],
                  ]
              ),
              values=np.array([1, 2, 3, 4, 5, 6, 7]),
              dense_shape=np.array([3, 4]),
          )
      )
      expected_sparse_tensor_values = [
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0]]),
              values=np.array([1]),
              dense_shape=np.array([1, 1]),
          ),
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0], [0, 1], [0, 2], [0, 3]]),
              values=np.array([2, 3, 4, 5]),
              dense_shape=np.array([1, 4]),
          ),
          tf.compat.v1.SparseTensorValue(
              indices=np.array([[0, 0], [0, 1]]),
              values=np.array([6, 7]),
              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 4 for calling the UtilTest obj's underlying member method code with example usage: obj.testSplitTensorValueSparseVarLen() without return types