code: def test_correctness(self):
      layer = layers.HashedCrossing(num_bins=5)
      feat1 = np.array(["A", "B", "A", "B", "A"])
      feat2 = np.array([101, 101, 101, 102, 102])
      output = layer((feat1, feat2))
      self.assertAllClose(tf.constant([1, 4, 1, 1, 3]), output)
  
      layer = layers.HashedCrossing(num_bins=5, output_mode="one_hot")
      feat1 = np.array(["A", "B", "A", "B", "A"])
      feat2 = np.array([101, 101, 101, 102, 102])
      output = layer((feat1, feat2))
      self.assertAllClose(
          np.array(
              [
                  [0.0, 1.0, 0.0, 0.0, 0.0],
                  [0.0, 0.0, 0.0, 0.0, 1.0],
                  [0.0, 1.0, 0.0, 0.0, 0.0],
                  [0.0, 1.0, 0.0, 0.0, 0.0],
                  [0.0, 0.0, 0.0, 1.0, 0.0],
              ]
          ),
          output,
      )
  
file_path: keras/keras/layers/preprocessing/hashed_crossing_test.py
imports: import numpy
  import pytest
  import tensorflow
  from keras import backend
  from keras import layers
  from keras import testing
label_desc: Use image node_id 2 for calling the HashedCrossingTest obj's underlying member method code with example usage: obj.test_correctness() without return types