code: def test_normalization_basics(self):
      self.run_layer_test(
          layers.Normalization,
          init_kwargs={
              "axis": -1,
          },
          input_shape=(2, 3),
          expected_output_shape=(2, 3),
          expected_num_trainable_weights=0,
          expected_num_non_trainable_weights=3,
          expected_num_seed_generators=0,
          expected_num_losses=0,
          supports_masking=True,
      )
      self.run_layer_test(
          layers.Normalization,
          init_kwargs={
              "axis": -1,
              "mean": np.array([0.5, 0.2, -0.1]),
              "variance": np.array([0.1, 0.2, 0.3]),
          },
          input_shape=(2, 3),
          expected_output_shape=(2, 3),
          expected_num_trainable_weights=0,
          expected_num_non_trainable_weights=0,
          expected_num_seed_generators=0,
          expected_num_losses=0,
          supports_masking=True,
      )
      self.run_layer_test(
          layers.Normalization,
          init_kwargs={
              "axis": -1,
              "mean": np.array([0.5, 0.2, -0.1]),
              "variance": np.array([0.1, 0.2, 0.3]),
              "invert": True,
          },
          input_shape=(2, 3),
          expected_output_shape=(2, 3),
          expected_num_trainable_weights=0,
          expected_num_non_trainable_weights=0,
          expected_num_seed_generators=0,
          expected_num_losses=0,
          supports_masking=True,
      )
  
file_path: keras/keras/layers/preprocessing/normalization_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 1 for calling the NormalizationTest obj's underlying member method code with example usage: obj.test_normalization_basics() without return types