code: def test_random_crop_full(self):
      np.random.seed(1337)
      height, width = 8, 16
      if backend.config.image_data_format() == "channels_last":
          input_shape = (12, 8, 16, 3)
      else:
          input_shape = (12, 3, 8, 16)
      inp = np.random.random(input_shape)
      layer = layers.RandomCrop(height, width)
      actual_output = layer(inp, training=False)
      self.assertAllClose(inp, actual_output)
  
file_path: keras/keras/layers/preprocessing/random_crop_test.py
imports: import numpy
  from tensorflow import data
  from keras import backend
  from keras import layers
  from keras import testing
label_desc: Use image node_id 2 for calling the RandomCropTest obj's underlying member method code with example usage: obj.test_random_crop_full() without return types