code: def testBasic(self):
      components = np.random.randint(12, size=(100,)).astype(np.int32)
      dataset = (
          dataset_ops.Dataset.from_tensor_slices(components)
          .map(lambda x: array_ops.fill([x], x))
          .apply(batching.dense_to_sparse_batch(4, [12]))
      )
      get_next = self.getNext(dataset)
  
      for start in range(0, len(components), 4):
          results = self.evaluate(get_next())
          self.assertAllEqual(
              [
                  [i, j]
                  for i, c in enumerate(components[start : start + 4])
                  for j in range(c)
              ],
              results.indices,
          )
          self.assertAllEqual(
              [
                  c
                  for c in components[start : start + 4]
                  for _ in range(c)
              ],
              results.values,
          )
          self.assertAllEqual(
              [min(4, len(components) - start), 12], results.dense_shape
          )
  
      with self.assertRaises(errors.OutOfRangeError):
          self.evaluate(get_next())
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import batching
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the DenseToSparseBatchTest obj's underlying member method code with example usage: obj.testBasic() without return types