code: def test_random_translation_up_numeric_constant(self, data_format):
      input_image = np.arange(0, 25).astype("float32")
      # Shifting by -.2 * 5 = 1 pixel.
      expected_output = np.asarray(
          [
              [5, 6, 7, 8, 9],
              [10, 11, 12, 13, 14],
              [15, 16, 17, 18, 19],
              [20, 21, 22, 23, 24],
              [0, 0, 0, 0, 0],
          ]
      )
      if data_format == "channels_last":
          input_image = np.reshape(input_image, (1, 5, 5, 1))
          expected_output = backend.convert_to_tensor(
              np.reshape(expected_output, (1, 5, 5, 1)), dtype="float32"
          )
      else:
          input_image = np.reshape(input_image, (1, 1, 5, 5))
          expected_output = backend.convert_to_tensor(
              np.reshape(expected_output, (1, 1, 5, 5)), dtype="float32"
          )
      self.run_layer_test(
          layers.RandomTranslation,
          init_kwargs={
              "height_factor": (-0.2, -0.2),
              "width_factor": 0.0,
              "fill_mode": "constant",
              "data_format": data_format,
          },
          input_shape=None,
          input_data=input_image,
          expected_output=expected_output,
          supports_masking=False,
          run_training_check=False,
      )
  
file_path: keras/keras/layers/preprocessing/random_translation_test.py
imports: import numpy
  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 5 for calling the RandomTranslationTest obj's underlying member method code with example usage: obj.test_random_translation_up_numeric_constant(data_format) without return types