code: def testPaddedBatchDatasetShapeSpecifications(self):
      int_placeholder = array_ops.placeholder(dtypes.int32)
      float_placeholder = array_ops.placeholder(dtypes.float32)
      string_placeholder = array_ops.placeholder(dtypes.string)
      input_dataset = dataset_ops.Dataset.from_tensors(
          (int_placeholder, float_placeholder, string_placeholder)
      )
  
      # Test different ways of specifying the `padded_shapes` argument.
      dynamic_padding_from_tensor_shapes = input_dataset.padded_batch(
          32,
          padded_shapes=(
              tensor_shape.TensorShape([None]),
              tensor_shape.TensorShape([None, None]),
              tensor_shape.TensorShape([37]),
          ),
      )
      dynamic_padding_from_lists = input_dataset.padded_batch(
          32, padded_shapes=([None], [None, None], [37])
      )
      dynamic_padding_from_lists_with_minus_one = (
          input_dataset.padded_batch(
              32, padded_shapes=([-1], [-1, -1], [37])
          )
      )
      dynamic_padding_from_tensors = input_dataset.padded_batch(
          32,
          padded_shapes=(
              constant_op.constant([-1], dtype=dtypes.int64),
              constant_op.constant([-1, -1], dtype=dtypes.int64),
              constant_op.constant([37], dtype=dtypes.int64),
          ),
      )
  
      for dataset in [
          dynamic_padding_from_tensor_shapes,
          dynamic_padding_from_lists,
          dynamic_padding_from_lists_with_minus_one,
          dynamic_padding_from_tensors,
      ]:
          dataset_output_shapes = dataset_ops.get_legacy_output_shapes(
              dataset
          )
          self.assertEqual(
              [None, None], dataset_output_shapes[0].as_list()
          )
          self.assertEqual(
              [None, None, None], dataset_output_shapes[1].as_list()
          )
          self.assertEqual(
              [None, 37], dataset_output_shapes[2].as_list()
          )
  
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 11 for calling the PaddedBatchTest obj's underlying member method code with example usage: obj.testPaddedBatchDatasetShapeSpecifications() without return types