code: def testNonDefaultPadding(self, verify_fn):
      def build_dataset(seq_lens):
          def fill_tuple(x):
              filled = array_ops.fill([x], x)
              return (filled, string_ops.as_string(filled))
  
          padded_shape = [-1]
          return (
              dataset_ops.Dataset.from_tensor_slices(seq_lens)
              .map(fill_tuple)
              .padded_batch(
                  batch_size=4,
                  padded_shapes=(padded_shape, padded_shape),
                  padding_values=(-1, "<end>"),
              )
          )
  
      seq_lens = np.random.randint(1, 20, size=(32,)).astype(np.int32)
      verify_fn(self, lambda: build_dataset(seq_lens), num_outputs=8)
  
imports: from absl.testing import parameterized
  import numpy
  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.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_tensor_value
  from tensorflow.python.platform import test
  from tensorflow.python.util import compat
label_desc: Use image node_id 2 for calling the PaddedBatchCheckpointTest obj's underlying member method code with example usage: obj.testNonDefaultPadding(verify_fn) and returns: dataset_ops, filled,  string_ops