code: def _dynamicPad(self, bucket, window, window_size):
      # TODO(mrry): To match `tf.contrib.training.bucket()`, implement a
      # generic form of padded_batch that pads every component
      # dynamically and does not rely on static shape information about
      # the arguments.
      return dataset_ops.Dataset.zip(
          (
              dataset_ops.Dataset.from_tensors(bucket),
              window.padded_batch(
                  32,
                  (
                      tensor_shape.TensorShape([]),
                      tensor_shape.TensorShape([None]),
                      tensor_shape.TensorShape([3]),
                  ),
              ),
          )
      )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.core.lib.core import error_codes_pb2
  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 constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  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.platform import test
label_desc: Use image node_id 1 for calling the GroupByWindowTest obj's underlying member method code with example usage: obj._dynamicPad(bucket, window, window_size) and returns: dataset_ops