code: def test_default_with_dict(self):
      features = [
          {"label": i, "inputs": [0, 1, 2, 3, 4, 5]} for i in range(8)
      ]
      batch = default_data_collator(features, return_tensors="tf")
      self.assertEqual(batch["labels"].numpy().tolist(), list(range(8)))
      self.assertEqual(batch["labels"].dtype, tf.int64)
      self.assertEqual(batch["inputs"].shape.as_list(), [8, 6])
  
      # With label_ids
      features = [
          {"label_ids": [0, 1, 2], "inputs": [0, 1, 2, 3, 4, 5]}
          for i in range(8)
      ]
      batch = default_data_collator(features, return_tensors="tf")
      self.assertEqual(
          batch["labels"].numpy().tolist(), ([[0, 1, 2]] * 8)
      )
      self.assertEqual(batch["labels"].dtype, tf.int64)
      self.assertEqual(batch["inputs"].shape.as_list(), [8, 6])
  
      # Features can already be tensors
      features = [
          {"label": i, "inputs": np.random.randint(0, 10, [10])}
          for i in range(8)
      ]
      batch = default_data_collator(features, return_tensors="tf")
      self.assertEqual(
          batch["labels"].numpy().tolist(), (list(range(8)))
      )
      self.assertEqual(batch["labels"].dtype, tf.int64)
      self.assertEqual(batch["inputs"].shape.as_list(), [8, 10])
  
      # Labels can already be tensors
      features = [
          {
              "label": np.array(i),
              "inputs": np.random.randint(0, 10, [10]),
          }
          for i in range(8)
      ]
      batch = default_data_collator(features, return_tensors="tf")
      self.assertEqual(batch["labels"].dtype, tf.int64)
      self.assertEqual(batch["labels"].numpy().tolist(), list(range(8)))
      self.assertEqual(batch["labels"].dtype, tf.int64)
      self.assertEqual(batch["inputs"].shape.as_list(), [8, 10])
  
imports: import os
  import shutil
  import tempfile
  import unittest
  import numpy
  from transformers import BertTokenizer, DataCollatorForLanguageModeling, DataCollatorForPermutationLanguageModeling, DataCollatorForTokenClassification, DataCollatorForWholeWordMask, DataCollatorWithPadding, default_data_collator, is_tf_available, is_torch_available, set_seed
  from transformers.testing_utils import require_tf, require_torch
label_desc: Use image node_id 3 for calling the TFDataCollatorIntegrationTest obj's underlying member method code with example usage: obj.test_default_with_dict() without return types