docstr: Output should equal resizing with crop_to_aspect ratio.
docstr_tok: ["Output","should","equal","resizing","with","crop_to_aspect","ratio","."]
code: def test_input_smaller_than_crop_box(self, size, data_format):
      """Output should equal resizing with crop_to_aspect ratio."""
      # batched case
      if data_format == "channels_first":
          img = np.random.random((2, 3, 9, 11))
      else:
          img = np.random.random((2, 9, 11, 3))
      out = layers.CenterCrop(
          size[0],
          size[1],
          data_format=data_format,
      )(img)
      ref_out = layers.Resizing(
          size[0],
          size[1],
          data_format=data_format,
          crop_to_aspect_ratio=True,
      )(img)
      self.assertAllClose(ref_out, out)
  
      # unbatched case
      if data_format == "channels_first":
          img = np.random.random((3, 9, 11))
      else:
          img = np.random.random((9, 11, 3))
      out = layers.CenterCrop(
          size[0],
          size[1],
          data_format=data_format,
      )(img)
      ref_out = layers.Resizing(
          size[0],
          size[1],
          data_format=data_format,
          crop_to_aspect_ratio=True,
      )(img)
      self.assertAllClose(ref_out, out)
  
file_path: keras/keras/layers/preprocessing/center_crop_test.py
imports: import numpy
  import pytest
  from absl.testing import parameterized
  from tensorflow import data
  from keras import backend
  from keras import layers
  from keras import testing
label_desc: Use image node_id 4 for calling the CenterCropTest obj's underlying member method code with example usage: obj.test_input_smaller_than_crop_box(size, data_format) without return types