code: def test_masking_correctness(self):
      x = np.array(
          [
              [[0.0, 0.0], [1.0, 2.0], [0.0, 0.0]],
              [[2.0, 2.0], [0.0, 0.0], [2.0, 1.0]],
          ]
      )
      expected_mask = [[False, True, False], [True, False, True]]
  
      layer = layers.Masking(mask_value=0.0)
      self.assertAllClose(layer.compute_mask(x), expected_mask)
  
      test_obj = self
  
      class TestLayer(layers.Layer):
          def __init__(self, **kwargs):
              super().__init__(**kwargs)
              self.supports_masking = True
  
          def compute_output_shape(self, input_shape):
              return input_shape
  
          def call(self, inputs, mask=None):
              assert mask is not None
              test_obj.assertAllClose(mask, expected_mask)
              return inputs
  
      model = models.Sequential(
          [
              layers.Masking(mask_value=0.0),
              TestLayer(),
          ]
      )
      model(x)
  
file_path: keras/keras/layers/core/masking_test.py
imports: import numpy
  import pytest
  from keras import layers
  from keras import models
  from keras import testing
label_desc: Use image node_id 2 for calling the MaskingTest obj's underlying member method code with example usage: obj.test_masking_correctness() and returns: input_shape, inputs