code: def test_correctness_static(
      self,
      layer_class,
      np_op,
      init_kwargs={},
      input_shape=(2, 4, 5),
      expected_output_shape=(2, 4, 5),
      skip_mask_test=False,
  ):
      batch_size = input_shape[0]
      shape = input_shape[1:]
      x1 = np.random.rand(*input_shape)
      x2 = np.random.rand(*input_shape)
      x3 = np_op(x1, x2, **init_kwargs)
  
      input_1 = layers.Input(shape=shape, batch_size=batch_size)
      input_2 = layers.Input(shape=shape, batch_size=batch_size)
      layer = layer_class(**init_kwargs)
      out = layer([input_1, input_2])
      model = models.Model([input_1, input_2], out)
      res = model([x1, x2])
  
      self.assertEqual(res.shape, expected_output_shape)
      self.assertAllClose(res, x3, atol=1e-4)
      self.assertIsNone(
          layer.compute_mask([input_1, input_2], [None, None])
      )
      if not skip_mask_test:
          self.assertTrue(
              np.all(
                  backend.convert_to_numpy(
                      layer.compute_mask(
                          [input_1, input_2],
                          [backend.Variable(x1), backend.Variable(x2)],
                      )
                  )
              )
          )
  
file_path: keras/keras/layers/merging/merging_test.py
imports: import numpy
  import pytest
  from absl.testing import parameterized
  from keras import backend
  from keras import layers
  from keras import models
  from keras import testing
label_desc: Use image node_id 2 for calling the MergingLayersTest obj's underlying member method code with example usage: obj.test_correctness_static(layer_class, np_op, init_kwargs, input_shape, expected_output_shape, skip_mask_test) without return types