code: def test_tf_data_compatibility(self):
      # Test 3D input: shape (2, 1, 3)
      layer = layers.RandomFlip("vertical", seed=42)
      input_data = np.array([[[2, 3, 4]], [[5, 6, 7]]])
      expected_output = np.array([[[5, 6, 7]], [[2, 3, 4]]])
      ds = (
          tf_data.Dataset.from_tensor_slices(input_data)
          .batch(2)
          .map(layer)
      )
      for output in ds.take(1):
          output = output.numpy()
      self.assertAllClose(output, expected_output)
      # Test 4D input: shape (2, 2, 1, 3)
      layer = layers.RandomFlip("vertical", seed=42)
      input_data = np.array(
          [
              [
                  [[2, 3, 4]],
                  [[5, 6, 7]],
              ],
              [
                  [[2, 3, 4]],
                  [[5, 6, 7]],
              ],
          ]
      )
      expected_output = np.array(
          [
              [[[5, 6, 7]], [[2, 3, 4]]],
              [[[5, 6, 7]], [[2, 3, 4]]],
          ]
      )
      ds = (
          tf_data.Dataset.from_tensor_slices(input_data)
          .batch(2)
          .map(layer)
      )
      for output in ds.take(1):
          output = output.numpy()
      self.assertAllClose(output, expected_output)
  
file_path: keras/keras/layers/preprocessing/random_flip_test.py
imports: import unittest.mock
  import numpy
  from absl.testing import parameterized
  from tensorflow import data
  from keras import backend
  from keras import layers
  from keras import testing
  from keras import utils
label_desc: Use image node_id 4 for calling the RandomFlipTest obj's underlying member method code with example usage: obj.test_tf_data_compatibility() without return types