code: def testShapeErrors(self):
      def dataset_fn(input_tensor):
          return dataset_ops.Dataset.from_tensors(input_tensor).apply(
              batching.dense_to_sparse_batch(4, [12])
          )
  
      # Initialize with an input tensor of incompatible rank.
      get_next = self.getNext(dataset_fn([[1]]))
      with self.assertRaisesRegex(
          errors.InvalidArgumentError, "incompatible with the row shape"
      ):
          self.evaluate(get_next())
  
      # Initialize with an input tensor that is larger than `row_shape`.
      get_next = self.getNext(dataset_fn(np.int32(range(13))))
      with self.assertRaisesRegex(
          errors.DataLossError, "larger than the row shape"
      ):
          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 4 for calling the DenseToSparseBatchTest obj's underlying member method code with example usage: obj.testShapeErrors() and returns: dataset_ops