code: def test_padding_accepts_tensors_tf(self):
      import tensorflow as tf
  
      features = [
          {"input_ids": tf.constant([0, 1, 2])},
          {"input_ids": tf.constant([0, 1, 2, 3])},
      ]
      tokenizer = BertTokenizer.from_pretrained("bert-base-cased")
  
      batch = tokenizer.pad(features, padding=True)
      self.assertTrue(isinstance(batch["input_ids"], tf.Tensor))
      self.assertEqual(
          batch["input_ids"].numpy().tolist(),
          [[0, 1, 2, tokenizer.pad_token_id], [0, 1, 2, 3]],
      )
      batch = tokenizer.pad(features, padding=True, return_tensors="tf")
      self.assertTrue(isinstance(batch["input_ids"], tf.Tensor))
      self.assertEqual(
          batch["input_ids"].numpy().tolist(),
          [[0, 1, 2, tokenizer.pad_token_id], [0, 1, 2, 3]],
      )
  
imports: import os
  import pickle
  import tempfile
  import unittest
  from typing import Callable, Optional
  import numpy
  from transformers import PreTrainedTokenizerFast
  from transformers import BatchEncoding, BertTokenizer, BertTokenizerFast, PreTrainedTokenizer, TensorType, TokenSpan, is_tokenizers_available
  from transformers.models.gpt2.tokenization_gpt2 import GPT2Tokenizer
  from transformers.testing_utils import CaptureStderr, require_flax, require_tf, require_tokenizers, require_torch, slow
label_desc: Use image node_id 16 for calling the TokenizerUtilsTest obj's underlying member method code with example usage: obj.test_padding_accepts_tensors_tf() without return types